| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme
Abstract general class for testing schemes in Weka.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme
Abstract general class for testing schemes in Weka.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| ThreadSafe
Interface to something that is thread safe
|
| Class and Description |
|---|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme
Abstract general class for testing schemes in Weka.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| DistanceFunction
Interface for any class that can compute and return distances between two
instances.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Instance
Interface representing an instance.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| Attribute
Class for handling an attribute.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Summarizable
Interface to something that provides a short textual summary (as opposed
to toString() which is usually a fairly complete description) of itself.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme
Abstract general class for testing schemes in Weka.
|
| Copyable
Interface implemented by classes that can produce "shallow" copies
of their objects.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| PartitionGenerator
This interface can be implemented by algorithms that generate
a partition of the instance space (e.g., decision trees).
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Summarizable
Interface to something that provides a short textual summary (as opposed
to toString() which is usually a fairly complete description) of itself.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Attribute
Class for handling an attribute.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Copyable
Interface implemented by classes that can produce "shallow" copies
of their objects.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Summarizable
Interface to something that provides a short textual summary (as opposed
to toString() which is usually a fairly complete description) of itself.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Matchable
Interface to something that can be matched with tree matching
algorithms.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| PartitionGenerator
This interface can be implemented by algorithms that generate
a partition of the instance space (e.g., decision trees).
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Summarizable
Interface to something that provides a short textual summary (as opposed
to toString() which is usually a fairly complete description) of itself.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| WekaException
Class for Weka-specific exceptions.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| BatchPredictor
Interface to something that can produce predictions in a batch manner
when presented with a set of Instances.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme
Abstract general class for testing schemes in Weka.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| DistanceFunction
Interface for any class that can compute and return distances between two
instances.
|
| Drawable
Interface to something that can be drawn as a graph.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| NormalizableDistance
Represents the abstract ancestor for normalizable distance functions, like
Euclidean or Manhattan distance.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| AbstractInstance
Abstract class providing common functionality for the original instance
implementations.
|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| AlgVector
Class for performing operations on an algebraic vector
of floating-point values.
|
| Attribute
Class for handling an attribute.
|
| AttributeLocator
This class locates and records the indices of a certain type of attributes,
recursively in case of Relational attributes.
|
| AttributeStats
A Utility class that contains summary information on an
the values that appear in a dataset for a particular attribute.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| Capabilities.Capability
enumeration of all capabilities
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| Check
Abstract general class for testing in Weka.
|
| CheckScheme.PostProcessor
a class for postprocessing the test-data
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Copyable
Interface implemented by classes that can produce "shallow" copies
of their objects.
|
| CustomDisplayStringProvider
For classes that do not implement the OptionHandler interface and want to
provide a custom display string in the GenericObjectEditor, which is more
descriptive than the class name.
|
| Debug.Clock
A little helper class for clocking and outputting times.
|
| Debug.Log
A helper class for logging stuff.
|
| Debug.Timestamp
A class that can be used for timestamps in files, The toString() method
simply returns the associated Date object in a timestamp format.
|
| Defaults
Base class for providing a set of default settings for an application.
|
| DictionaryBuilder
Class for building and maintaining a dictionary of terms.
|
| DistanceFunction
Interface for any class that can compute and return distances between two
instances.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| FastVector
Deprecated.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Javadoc
Abstract superclass for classes that generate Javadoc comments and replace
the content between certain comment tags.
|
| Matrix
Deprecated.
Use
weka.core.matrix.Matrix instead - only for
backwards compatibility. |
| NominalAttributeInfo
Stores information for nominal and string attributes.
|
| NormalizableDistance
Represents the abstract ancestor for normalizable distance functions, like
Euclidean or Manhattan distance.
|
| Optimization
Implementation of Active-sets method with BFGS update to solve optimization
problem with only bounds constraints in multi-dimensions.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| PropertyPath.Path
Contains a (property) path structure
|
| PropertyPath.PathElement
Represents a single element of a property path
|
| ProtectedProperties
Simple class that extends the Properties class so that the properties are
unable to be modified.
|
| Range
Class representing a range of cardinal numbers.
|
| RevisionHandler
For classes that should return their source control revision.
|
| RevisionUtils.Type
Enumeration of source control types.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| SparseInstance
Class for storing an instance as a sparse vector.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformation.Field
the possible fields
|
| TechnicalInformation.Type
the different types of information
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| TestInstances
Generates artificial datasets for testing.
|
| Trie.TrieNode
Represents a node in the trie.
|
| WekaException
Class for Weka-specific exceptions.
|
| WekaPackageClassLoaderManager
Class that manages classloaders from individual Weka plugin packages.
|
| WekaPackageLibIsolatingClassLoader
A ClassLoader that loads/finds classes from one Weka plugin package.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| DistanceFunction
Interface for any class that can compute and return distances between two
instances.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| DistanceFunction
Interface for any class that can compute and return distances between two
instances.
|
| EuclideanDistance
Implementing Euclidean distance (or similarity) function.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| EuclideanDistance
Implementing Euclidean distance (or similarity) function.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Defaults
Base class for providing a set of default settings for an application.
|
| Settings
Maintains a collection of settings.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| Range
Class representing a range of cardinal numbers.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Aggregateable
Interface to something that can aggregate an object of the same type with
itself.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| AdditionalMeasureProducer
Interface to something that can produce measures other than those
calculated by evaluation modules.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Range
Class representing a range of cardinal numbers.
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| RevisionHandler
For classes that should return their source control revision.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| PartitionGenerator
This interface can be implemented by algorithms that generate
a partition of the instance space (e.g., decision trees).
|
| RevisionHandler
For classes that should return their source control revision.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| DictionaryBuilder
Class for building and maintaining a dictionary of terms.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| Range
Class representing a range of cardinal numbers.
|
| RevisionHandler
For classes that should return their source control revision.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| CapabilitiesHandler
Classes implementing this interface return their capabilities in regards
to datasets.
|
| CapabilitiesIgnorer
Classes implementing this interface make it possible to turn off
capabilities checking.
|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Randomizable
Interface to something that has random behaviour that is able to be
seeded with an integer.
|
| RevisionHandler
For classes that should return their source control revision.
|
| WeightedAttributesHandler
Interface to something that makes use of the information provided
by attribute weights.
|
| WeightedInstancesHandler
Interface to something that makes use of the information provided
by instance weights.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| Defaults
Base class for providing a set of default settings for an application.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| SelectedTag
Represents a selected value from a finite set of values, where each
value is a Tag (i.e. has some string associated with it).
|
| Settings
Maintains a collection of settings.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Undoable
Interface implemented by classes that support undo.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| RevisionHandler
For classes that should return their source control revision.
|
| Tag
A
Tag simply associates a numeric ID with a String description. |
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| TechnicalInformation
Used for paper references in the Javadoc and for BibTex generation.
|
| TechnicalInformationHandler
For classes that are based on some kind of publications.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| Capabilities
A class that describes the capabilites (e.g., handling certain types of
attributes, missing values, types of classes, etc.) of a specific classifier.
|
| Defaults
Base class for providing a set of default settings for an application.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| Class and Description |
|---|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Class and Description |
|---|
| Defaults
Base class for providing a set of default settings for an application.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Settings
Maintains a collection of settings.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| WekaException
Class for Weka-specific exceptions.
|
| Class and Description |
|---|
| Defaults
Base class for providing a set of default settings for an application.
|
| EnvironmentHandler
Interface for something that can utilize environment
variables.
|
| Settings
Maintains a collection of settings.
|
| WekaException
Class for Weka-specific exceptions.
|
| Class and Description |
|---|
| Option
Class to store information about an option.
|
| OptionHandler
Interface to something that understands options.
|
| Class and Description |
|---|
| RevisionHandler
For classes that should return their source control revision.
|
| Class and Description |
|---|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| Defaults
Base class for providing a set of default settings for an application.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Settings
Maintains a collection of settings.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| Class and Description |
|---|
| Attribute
Class for handling an attribute.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| Class and Description |
|---|
| CommandlineRunnable
Interface to something that can be run from the command line.
|
| Defaults
Base class for providing a set of default settings for an application.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| LogHandler
Interface to something that can output messages to a log
|
| RevisionHandler
For classes that should return their source control revision.
|
| Settings
Maintains a collection of settings.
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| WekaException
Class for Weka-specific exceptions.
|
| Class and Description |
|---|
| Defaults
Base class for providing a set of default settings for an application.
|
| Environment
This class encapsulates a map of all environment and java system properties.
|
| Instance
Interface representing an instance.
|
| Instances
Class for handling an ordered set of weighted instances.
|
| OptionMetadata
Method annotation that can be used with scheme parameters to provide a nice
display-ready name for the parameter, help information and, if applicable,
command line option details
|
| Settings.SettingKey
Class implementing a key for a setting.
|
| WekaException
Class for Weka-specific exceptions.
|
Copyright © 2018 University of Waikato, Hamilton, NZ. All Rights Reserved.


Client-Side Development (alpha 2)
Getting Started
Spin Up An Instance
You can currently run Coronium GS via an Amazon AMI, or Ubuntu 14.04 64bit based install. DigitalOcean is the recommended cloud provider for Ubuntu based instances.
The most current installation options can be found at the Coronium GS site.
See also: Server side development
Download the source
Visit the bitbucket repo to download the latest development bundle for Coronium GS.
Overview: main.lua
The main.lua file that is included in the download (Client/main.lua) represents a template with all the possible client events included (see also: main-tpl.lua ). The file is more of a reference -- study it -- you can use it to do development testing before creating your app within a Composer based structure.
For a full listing of client events you can listen for see: Client-side Events
At the very minimum, you need to require the Coronium GS Client into your file:
local gs = require( 'gs.CoroniumGSClient' ):new()
Connections
Connecting
Open the Client/main.lua and enter your Coronium GS information at the bottom of the file, in a connection_table:
local connection = { host = 'your.gs.instance', port = 7173, handle = 'SuperUser', data = { facebookId = "123-books" }, key = 'abc', ping = true } gs:connect( connection )
For more information on the connect method see the connect.
Reconnecting
To reconnect to the server, prehaps after a game has ended, or the client has dropped off for some reason, use the reconnect client method.
For example, to reconnect on a 'game done' event:
local function onClientData( event ) if event.data.game_done then --custom msg from server gs:reconnect() end end gs.events:on( "ClientData", onClientData )
Messaging
The Coronium GS model is built around messaging events. To send a message to the server, you use the send method:
local function onClientData( event ) gs:send( { msg = "Hello server" } ) end gs.events:on( "ClientData", onClientData )
The messaging protocol is completely up to you. Just be sure to wrap the data up in a table and then send it with the send method.
Events
Coronium GS is an event driven system. You listen for specific events and then perform some action depending on the data passed into these events. To listen for events, we need an event handler, and the listener.
GameStart
The GameStart event is called all the players have connected together are ready to start the game. We can listen for the event like so:
local function onGameStart( event ) print( "game started!" ) end gs.events:on( 'GameStart', onGameStart )
This event contains keyed data that we can use. Some of the results passed back from the GameStart event are:
local function onGameStart( event ) local d = event.data local player_name = d.player_name -- The players name. local player_num = d.player_num -- The players position. local players_info = d.players_info -- An array of each players info. for _, player in ipairs( players_info ) do p( player.player_num .. ": " .. player.player_name ) end end gs.events:on( "GameStart", onGameStart )
Use the Pretty Print to see the exact results.
ClientData
The 'work horse' of Coronium GS, the ClientData event is called when the client has recieved data from the server. You can capture and process this data to make your game do stuff.
local function onClientData( event ) if event.data.move_player then player.x = event.data.x end end gs.events:on( "ClientData", onClientData )
GameData
The GameData event is another important event that delivers the current persistent 'game object'.
local function onGameData( event ) p( event.data ) end gs.events:on( "GameData", onGameData )
You can also specifically call for the game data object with the getData method:
--== Set up the listener local function onGameData( event ) p( event.data ) end gs.events:on( "GameData", onGameData ) --== Tell the server to send down data object gs:getData()
For a full listing of client events you can listen for see: Client-side Events
Custom Events
The Coronium GS Client comes packaged with the awesome EventDispatcher module for Corona SDK.
You can use this module to create your own event emitters, just like the core Coronium GS client module.
my_module.lua
local dispatcher = require( 'gs.EventDispatcher' ) local my_module = {} my_module.events = dispatcher() function my_module:doSomething() self.events:emit( "DidSomething", { msg = "Oops, I did it again." } ) end return my_module
other.lua
local my_module = require( 'my_module' ) my_module.events:on( "DidSomething", function( event ) print( event.data.msg ) end) my_module:doSomething() --== Outputs: 'Oops, I did it again.'
Player Names/Handles
You can set a player name or "handle" in the connection table:
local conn_tbl = { host = 'ping.coronium.gs', port = '7173', handle = 'Chris', -- Handle/Player Name key = 'abc' } gs:connect( conn_tbl )
The "handle" can be any string identifier you'd like, and can be accessed with the server-side Client:getPlayerHandle, as well as the client-side getPlayerHandle.
On the server-side:
local function onClientData( client, data ) local handle = client:getPlayerHandle() end
On the client-side:
local function onClientData( event ) local handle = gs:getPlayerHandle() end
Check Game State
You can check if the game is currently in a running state with the isGameRunning method.
local function checkGameState() return gs:isGameRunning() --true or false end if checkGameState() then gs:send( { move = 1, pos = { 10, 10 } } ) else print( "Game no longer running" ) end
Pretty Print
The Coronium GS client has a built in pretty printer for incoming table data. This makes it real easy to visualize the incoming data for debugging purposes. To simplify its usage, you can 'localize' it as the method p -- which is the default on the server -- as follows:
local gs = require( 'gs.CoroniumGSClient' ):new() local p = gs.p --== Pretty Printer --== General usage p( some_table_data ) --== As debugging callback gs.events:on( "ClientData", p )
Using Composer
When using the Coronium GS client in a Composer Corona SDK based project, you need to 'globalize' the module.
To see a working example, open the demo project in the downloaded development bundle located in the demos/GS Composer Starter directory.
Demos
You can find a handful of demos in the development bundle download, in the demos folder. By studying those files, you can see more clearly how Coronium GS works in practice.
Client Docs
For a full listing of all available client methods and events, please see the Client Side Documentation.
Support
For support, tips, and community involvement, please visit the Coronium Cloud Community.
Coronium GS ©2014 Chris Byerley @develephant | develephant.net


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Enhanced stability and fluidity in droplet on hydrogel bilayers for measuring membrane protein diffusion.
We form artificial lipid bilayers suitable for single-molecule fluorescence microscopy by contacting an aqueous droplet with a hydrogel support immersed in a solution of lipid in oil. Our results show that droplet on hydrogel bilayers (DHBs) have high lipid mobilities, similar to those observed in unsupported lipid bilayers. DHBs are also stable over a period of several weeks. We examine membrane protein diffusion in these bilayers and report a decreased lateral mobility of the heptameric beta-barrel pore-forming toxin alpha-hemolysin versus that of its monomeric precursor. These results corroborate previous models of the alpha-hemolysin insertion mechanism where the monomer binds to the lipid bilayer without insertion.


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|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table1/table.png
|
| Antibody |
Species |
Catalogue number |
Dilution |
Source |
| CTb |
Goat |
703 |
1:5000 |
List biological |
| CTb |
Mouse |
ab35988 |
1:5000 |
Abcam |
| VGLUT2 |
Goat |
|
1:500 |
M. Watanabe |
| VGLUT2 |
Rabbit |
135 402 |
1:5000 |
Synaptic |
|
|
|
|
systems |
| CGRP |
Guinea |
T-5027 |
1:10,000 |
Bachem |
|
pig |
|
|
|
| Substance |
Rat |
OBT06435 |
1:200 |
Oxford biotech |
| P |
|
|
|
|
| NK1r |
Rabbit |
S8305 |
1:10,000 |
Sigma Aldrich |
| Fluorogold |
Guinea |
NM101 |
1:500 |
Protos biotech |
|
pig |
|
|
|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table1/table.svg.html
|
|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table2/table.png
|
| Rat |
VGLUT2 ^{+} |
CGRP ^{+} |
SP ^{+} |
VGLUT2 /CGRP^{+} ^{+} |
CGRP ^{+} |
with VGLUT2 |
| 1 |
74 |
13.3 |
3.7 |
9.3 |
70 |
| 2 |
78.7 |
9.7 |
1.7 |
9 |
93.1 |
| 3 |
72.3 |
11.3 |
1.7 |
7.3 |
64.7 |
| Mean |
75 |
11.4 |
2.3 |
8.6 |
75.9 |
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table2/table.svg.html
|
|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table3/table.png
|
| Rat |
Total projection cells |
NK1r ^{+} |
cells |
Giant cells |
NK1r-lacking cells |
NK1r ^{+} with contacts (%) |
cells |
NK1r-lacking cells with contacts (%) |
| 1 |
254 |
183 |
7 |
64 |
28 |
40.6 |
|
|
(72%) |
(2.8%) |
(25.2%) |
|
|
| 2 |
190 |
134 |
3 |
53 |
26.9 |
47.2 |
|
|
(70.5%) |
(1.6%) |
(27.9%) |
|
|
| 3 |
200 |
128 |
5 |
67 |
26.6 |
44.8 |
|
|
(64%) |
(2.5%) |
(33.5%) |
|
|
| 4 |
187 |
149 |
3 |
35 |
22.8 |
40 |
|
|
(80%) |
(1.6%) |
(18.7%) |
|
|
| Mean |
207.8 |
148.5 |
4.5 |
54.8 |
26.1 |
43.1 |
|
|
(71.6%) |
(2.1%) |
(26.3%) |
|
|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table3/table.svg.html
|
|
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table4/table.png
|
| Number |
Density |
Number |
Density |
Number |
Density |
Number |
Density |
| NK1r ^{+} |
(n = 18) |
43.6 |
8.5 |
3.2 |
0.6 |
140.7 |
26.6 |
87.7 |
16.8 |
|
|
(14–145) |
(2.8–24.3) |
(0–7) |
(0–1.5) |
(62–266) |
(16.7–43.1) |
(23–137) |
(9.3–31.8) |
| NK1r-lacking (n = 20) |
|
79.9 |
31.6 |
0.2 |
0.1 |
7.5 |
3.1 |
26.5 |
9.7 |
|
|
(30–210) |
(20.8–45.9) |
(0–2) |
(0–0.5) |
(2–15) |
(1.2–8) |
(5–99) |
(4–22.4) |
target/pdftable1/10.1016_j.pain.2014.08.023/tables/table4/table.svg.html
|


Combine the power of analog electronics, electromechanical systems and computer software.
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|
The RosenbergsJulius and Ethel RosenbergDuring and after World War II, Julius Rosenberg spied on behalf of the Soviet Union. His brother-in-law was a technician fabricating components for the Manhattan Project. Julius persuaded him to hand over atomic bomb secrets, which he then relayed to the U.S.S.R.Both Julius and his wife Ethel were arrested in 1950. J. Edgar Hoover called it the "crime of the century." In the end, they were convicted of conspiracy to commit espionage for the Soviets. The married couple was executed in the Electric Chair at Sing-Sing Prison. The Rosenbergs had been active members of the American Communist Party; Julius was chairman of Branch 16B of the Industrial Division, whose meetings were held in their apartment. They ostensibly quit the party in 1943 after Julius got a civilian job in the U.S. Army Signal Corps inspecting radar equipment. Then Julius met his KGB spymaster, Aleksandr Feklisov, for the first time. Over the next three years they had at least 50 such meetings, according to Feklisov. Julius handed over the schematic diagram for a lens mold, as well as a working specimen of a proximity fuse. Julius got this stuff from his brother-in-law, David Greenglass. When he got picked up by the FBI, Greenglass accused his older sister Ethel of typing up an incriminating report for the KGB. In all likelihood, it was probably David's wife Ruth. But why take your wife to prison, when you can send your sister instead? During a 2001 interview, Greenglass was unapologetic:
"I would not sacrifice my wife and my children for my sister. How do you like that? And that's what I told the FBI. I said, 'If you indict my wife, you can forget it. I'll never say a word about anybody.'"
timeline
|


McRae leads UC Riverside over Redlands 76-44
RIVERSIDE, Calif. (AP) - Callum McRae had 14 points and 10 rebounds to lead UC Riverside to a 76-44 win over Redlands on Thursday.
George Willborn III had 11 points for UC Riverside (3-2). Daniel Mading added 10 points. Zac Watson had eight rebounds for the home team.
Hass Berry had 15 points for the Bulldogs.
UC Riverside matches up against Denver at home on Saturday.
More AP college basketball: https://apnews.com/Collegebasketball and https://twitter.com/AP_Top25
This was generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com
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Cluster Serving
Programming Guide
Analytics Zoo Cluster Serving is a lightweight distributed, real-time serving solution that supports a wide range of deep learning models (such as TensorFlow, PyTorch, Caffe, BigDL and OpenVINO models). It provides a simple pub/sub API, so that the users can easily send their inference requests to the input queue (using a simple Python API); Cluster Serving will then automatically manage the scale-out and real-time model inference across a large cluster (using distributed streaming frameworks such as Apache Spark Streaming, Apache Flink, etc.)
The overall architecture of Analytics Zoo Cluster Serving solution is illustrated as below:
This page contains the guide for you to run Analytics Zoo Cluster Serving, including following:
Quick Start
This section provides a quick start example for you to run Analytics Zoo Cluster Serving. To simplify the example, we use docker to run Cluster Serving. If you do not have docker installed, install docker first. The quick start example contains all the necessary components so the first time users can get it up and running within minutes:
- A docker image for Analytics Zoo Cluster Serving (with all dependencies installed)
- A sample configuration file
- A sample trained TensorFlow model, and sample data for inference
- A sample Python client program
Use one command to run Cluster Serving container. (We provide quick start model in older version of docker image, for newest version, please refer to following sections and we remove the model to reduce the docker image size).
docker run --name cluster-serving -itd --net=host intelanalytics/zoo-cluster-serving:0.9.1
Log into the container using docker exec -it cluster-serving bash
, and run
cd cluster-serving
cluster-serving-init
zoo.jar
and config.yaml
is in your directory now.
Also, you can see prepared TensorFlow frozen ResNet50 model in resources/model
directory with following structure.
cluster-serving |
-- | model
-- frozen_graph.pb
-- graph_meta.json
Modify config.yaml
and add following to model
config
model:
path: resources/model
Start Cluster Serving using cluster-serving-start
.
Run python program python3 image_classification_and_object_detection_quick_start.py -i resources/test_image
to push data into queue and get inference result.
Then you can see the inference output in console.
cat prediction layer shape: (1000,)
the class index of prediction of cat image result: 292
cat prediction layer shape: (1000,)
Wow! You made it!
Note that the Cluster Serving quick start example will run on your local node only. Check the Deploy Your Own Cluster Serving section for how to configure and run Cluster Serving in a distributed fashion.
For more details, refer to following sections.
Workflow Overview
The figure below illustrates the simple 3-step "Prepare-Launch-Inference" workflow for Cluster Serving.
1. Install and prepare Cluster Serving environment on a local node:
- Copy a previously trained model to the local node; currently TensorFlow, PyTorch, Caffe, BigDL and OpenVINO models are supported.
- Install Analytics Zoo on the local node (e.g., using a single pip install command)
- Configure Cluster Server on the local node, including the file path to the trained model and the address of the cluster (such as Apache Hadoop YARN cluster, K8s cluster, etc.). Please note that you only need to deploy the Cluster Serving solution on a single local node, and NO modifications are needed for the (YARN or K8s) cluster.
2. Launch the Cluster Serving service
You can launch the Cluster Serving service by running the startup script on the local node. Under the hood, Cluster Serving will automatically deploy the trained model and serve the model inference requests across the cluster in a distributed fashion. You may monitor its runtime status (such as inference throughput) using TensorBoard.
3. Distributed, real-time (streaming) inference
Cluster Serving provides a simple pub/sub API to the users, so that you can easily send the inference requests to an input queue (currently Redis Streams is used) using a simple Python API.
Cluster Serving will then read the requests from the Redis stream, run the distributed real-time inference across the cluster (using Flink), and return the results back through Redis. As a result, you may get the inference results again using a simple Python API.
Deploy your Own Cluster Serving
1. Installation
It is recommended to install Cluster Serving by pulling the pre-built Docker image to your local node, which have packaged all the required dependencies. Alternatively, you may also manually install Cluster Serving (through either pip or direct downloading), Redis on the local node.
Docker
docker pull intelanalytics/zoo-cluster-serving
then, (or directly run docker run
, it will pull the image if it does not exist)
docker run --name cluster-serving -itd --net=host intelanalytics/zoo-cluster-serving:0.9.0
Log into the container
docker exec -it cluster-serving bash
cd ./cluster-serving
, you can see all the environments prepared.
Manual installation
Requirements
Non-Docker users need to install Flink 1.10.0+, 1.10.0 by default, Redis 5.0.0+, 5.0.5 by default.
For users do not have above dependencies, we provide following command to quickly set up.
Redis
$ export REDIS_VERSION=5.0.5
$ wget http://download.redis.io/releases/redis-${REDIS_VERSION}.tar.gz && \
tar xzf redis-${REDIS_VERSION}.tar.gz && \
rm redis-${REDIS_VERSION}.tar.gz && \
cd redis-${REDIS_VERSION} && \
make
Flink
$ export FLINK_VERSION=1.11.2
$ wget https://archive.apache.org/dist/flink/flink-${FLINK_VERSION}/flink-${FLINK_VERSION}-bin-scala_2.11.tgz && \
tar xzf flink-${FLINK_VERSION}-bin-scala_2.11.tgz && \
rm flink-${FLINK_VERSION}-bin-scala_2.11.tgz.tgz
After preparing dependencies above, make sure the environment variable $FLINK_HOME
(/path/to/flink-FLINK_VERSION-bin), $REDIS_HOME
(/path/to/redis-REDIS_VERSION) is set before following steps.
Install release version
pip install analytics-zoo-serving
Install nightly version
Download package from here, run following command to install Cluster Serving
pip install analytics_zoo_serving-*.whl
For users who need to deploy and start Cluster Serving, run cluster-serving-init
to download and prepare dependencies.
For users who need to do inference, aka. predict data only, the environment is ready.
2. Configuration
Set up cluster
Cluster Serving uses Flink cluster, make sure you have it according to Installation.
For docker user, the cluster should be already started. You could use netstat -tnlp | grep 8081
to check if Flink REST port is working, if not, call $FLINK_HOME/bin/start-cluster.sh
to start Flink cluster.
If you need to start Flink on yarn, refer to Flink on Yarn, or K8s, refer to Flink on K8s at Flink official documentation.
If you use Flink standalone, call $FLINK_HOME/bin/start-cluster.sh
to start Flink cluster.
Configuration file
After Installation, you will see a config file config.yaml
in your current working directory. This file contains all the configurations that you can customize for your Cluster Serving. See an example of config.yaml
below.
## Analytics Zoo Cluster Serving Config Example
# model path must be provided
modelPath: /path/to/model
Preparing Model
Currently Analytics Zoo Cluster Serving supports TensorFlow, OpenVINO, PyTorch, BigDL, Caffe models. Supported types are listed below.
You need to put your model file into a directory with layout like following according to model type, note that only one model is allowed in your directory. Then, set in config.yaml
file with modelPath:/path/to/dir
.
Tensorflow* Tensorflow SavedModel***
|-- model
|-- saved_model.pb
|-- variables
|-- variables.data-00000-of-00001
|-- variables.index
Tensorflow Frozen Graph
|-- model
|-- frozen_inference_graph.pb
|-- graph_meta.json
note: .pb
is the weight file which name must be frozen_inference_graph.pb
, .json
is the inputs and outputs definition file which name must be graph_meta.json
, with contents like {"input_names":["input:0"],"output_names":["output:0"]}
Tensorflow Checkpoint Please refer to freeze checkpoint example
Pytorch
|-- model
|-- xx.pt
Running Pytorch model needs extra dependency and config. Refer to here to install dependencies, and set environment variable $PYTHONHOME
to your python, e.g. python could be run by $PYTHONHOME/bin/python
and library is at $PYTHONHOME/lib/
.
OpenVINO
|-- model
|-- xx.xml
|-- xx.bin
BigDL
|--model
|-- xx.model
Caffe
|-- model
|-- xx.prototxt
|-- xx.caffemodel
Data Configuration
The field data
contains your input data configuration.
- src: the queue you subscribe for your input data, e.g. default config of Redis on local machine is
localhost:6379
. Note that please use the host address in your network instead of localhost or <IP_ADDRESS> when you run serving in cluster, and make sure other nodes in cluster could also recognize this address. - filter: the post-processing of pipeline, usually none, the model output would be returned. Except none, currently supported filters are,
Top-N, e.g. topN(1)
represents Top-1 result is kept and returned with index. User should follow this schema topN(n)
. Noted if the top-N number is larger than model output size of the the final layer, it would just return all the outputs.
Other Configuration
The field params
contains your inference parameter configuration.
- core_number: the batch size you use for model inference, usually the core number of your machine is recommended. Thus you could just provide your machine core number at this field. We recommend this value to be not smaller than 4 and not larger than 512. In general, using larger batch size means higher throughput, but also increase the latency between batches accordingly.
High Performance Configuration Recommended
Tensorflow, Pytorch
1 <= thread_per_model <= 8, in config
# default: number of models used in serving
# modelParallelism: core_number of your machine / thread_per_model
environment variable
export OMP_NUM_THREADS=thread_per_model
OpenVINO
environment variable
export OMP_NUM_THREADS=core_number of your machine
3. Launching Service
This section is about how to start and stop Cluster Serving.
Start
You can use following command to start Cluster Serving.
cluster-serving-start
Normally, when calling cluster-serving-start
, your config.yaml
should be in current directory. You can also use cluster-serving-start -c config_path
to pass config path config_path
to Cluster Serving manually.
Stop
You can use Flink UI in localhost:8081
by default, to cancel your Cluster Serving job.
Shut Down
You can use following command to shutdown Cluster Serving. This operation will stop all running services related to Cluster Serving. Note that your data in Redis will be removed when you shutdown.
cluster-serving-shutdown
If you are using Docker, you could also run docker rm
to shutdown Cluster Serving.
Start Multiple Serving
To run multiple Cluster Serving job, e.g. the second job name is serving2
, then use following configuration
# model path must be provided
# modelPath: /path/to/model
# name, default is serving_stream, you need to specify if running multiple servings
# jobName: serving2
then call cluster-serving-start
in this directory would start another Cluster Serving job with this new configuration.
Then, in Python API, pass name=serving2
argument during creating object, e.g.
input_queue=InputQueue(name=serving2)
output_queue=OutputQueue(name=serving2)
Then the Python API would interact with job serving2
.
HTTP Server (for sync API only)
If you want to use sync API for inference, you should start a provided HTTP server first. User can submit HTTP requests to the HTTP server through RESTful APIs. The HTTP server will parse the input requests and pub them to Redis input queues, then retrieve the output results and render them as json results in HTTP responses.
Prepare
User can download a analytics-zoo-${VERSION}-http.jar from the Nexus Repository with GAVP:
<groupId>com.intel.analytics.zoo</groupId>
<artifactId>analytics-zoo-bigdl_${BIGDL_VERSION}-spark_${SPARK_VERSION}</artifactId>
<version>${ZOO_VERSION}</version>
User can also build from the source code:
mvn clean package -P spark_2.4+ -Dmaven.test.skip=true
Start the HTTP Server
User can start the HTTP server with following command.
java -jar analytics-zoo-bigdl_${BIGDL_VERSION}-spark_${SPARK_VERSION}-${ZOO_VERSION}-http.jar
And check the status of the HTTP server with:
curl http://${BINDED_HOST_IP}:${BINDED_HOST_PORT}/
If you get a response like "welcome to analytics zoo web serving frontend", that means the HTTP server is started successfully.
Start options
User can pass options to the HTTP server when start it:
java -jar analytics-zoo-bigdl_${BIGDL_VERSION}-spark_${SPARK_VERSION}-${ZOO_VERSION}-http.jar --redisHost="<IP_ADDRESS>"
All the supported parameter are listed here: * interface: the binded server interface, default is "<IP_ADDRESS>" * port: the binded server port, default is 10020 * redisHost: the host IP of redis server, default is "localhost" * redisPort: the host port of redis server, default is 6379 * redisInputQueue: the input queue of redis server, default is "serving_stream" * redisOutputQueue: the output queue of redis server, default is "result:" * parallelism: the parallelism of requests processing, default is 1000 * timeWindow: the timeWindow wait to pub inputs to redis, default is 0 * countWindow: the timeWindow wait to ub inputs to redis, default is 56 * tokenBucketEnabled: the switch to enable/disable RateLimiter, default is false * tokensPerSecond: the rate of permits per second, default is 100 * tokenAcquireTimeout: acquires a permit from this RateLimiter if it can be obtained without exceeding the specified timeout(ms), default is 100
User can adjust these options to tune the performance of the HTTP server.
4. Model Inference
We support Python API and HTTP RESTful API for conducting inference with Data Pipeline in Cluster Serving.
Python API
For Python API, the requirements of python packages are opencv-python
(for raw image only), pyyaml
, redis
. You can use InputQueue
and OutputQueue
to connect to data pipeline by providing the pipeline url, e.g. my_input_queue = InputQueue(host, port)
and my_output_queue = OutputQueue(host, port)
. If parameters are not provided, default url localhost:6379
would be used.
We provide some basic usages here, for more details, please see API Guide.
Async API
Async API provide method to enqueue data, the method would not block and user can query the data anytime afterwards.
To input data to queue, you need a InputQueue
instance, and using enqueue
method, for each input, give a key correspond to your model or give arbitrary key if your model does not care about it.
To enqueue an image
from zoo.serving.client import InputQueue
input_api = InputQueue()
input_api.enqueue('my-image1', user_define_key={"path: 'path/to/image1'})
To enqueue an instance containing 1 image and 2 ndarray
from zoo.serving.client import InputQueue
import numpy as np
input_api = InputQueue()
t1 = np.array([1,2])
t2 = np.array([[1,2], [3,4]])
input_api.enqueue('my-instance', img={"path": 'path/to/image'}, tensor1=t1, tensor2=t2)
There are 4 types of inputs in total, string, image, tensor, sparse tensor, which could represents nearly all types of models. For more details of usage, go to API Guide
To get data from queue, you need a OutputQueue
instance, and using query
or dequeue
method. The query
method takes image uri as parameter and returns the corresponding result. The dequeue
method takes no parameter and just returns all results and also delete them in data queue. See following example.
from zoo.serving.client import OutputQueue
output_api = OutputQueue()
img1_result = output_api.query('img1')
all_result = output_api.dequeue() # the output queue is empty after this code
Consider the code above,
img1_result = output_api.query('img1')
Sync API
Sync API provide method to predict data, the method would block until the result is available.
User need to create a InputQueue
instance with sync=True
and frontend_url=frontend_server_url
argument.
from zoo.serving.client import InputQueue
input_api = InputQueue(sync=True, frontend_url=frontend_server_url)
response = input_api.predict(request_json_string)
print(response.text)
example of request_json_string
is
'{
"instances" : [ {
"ids" : [ 100.0, 88.0 ]
}]
}'
This API is also a python support of Restful API section, so for more details of input format, refer to it.
RESTful API
This part describes API endpoints and end-to-end examples on usage. The requests and responses are in JSON format. The composition of them depends on the requests type or verb. See the APIs for details. In case of error, all APIs will return a JSON object in the response body with error as key and the error message as the value:
{
"error": <error message string>
}
Predict API
URL
POST http://host:port/predict
Request Example for images as inputs:
curl -d \
'{
"instances": [
{
"image": "/9j/4AAQSkZJRgABAQEASABIAAD/7RcEUGhvdG9za..."
},
{
"image": "/9j/4AAQSkZJRgABAQEASABIAAD/7RcEUGhvdG9za..."
}
]
}' \
-X POST http://host:port/predict
Response Example
{
"predictions": [
"{value=[[903,0.1306194]]}",
"{value=[[903,0.1306194]]}"
]
}
Request Example for tensor as inputs:
curl -d \
'{
"instances" : [ {
"ids" : [ 100.0, 88.0 ]
}, {
"ids" : [ 100.0, 88.0 ]
} ]
}' \
-X POST http://host:port/predict
Response Example
{
"predictions": [
"{value=[[1,0.6427843]]}",
"{value=[[1,0.6427842]]}"
]
}
Another request example for composition of scalars and tensors.
curl -d \
'{
"instances" : [ {
"intScalar" : 12345,
"floatScalar" : 3.14159,
"stringScalar" : "hello, world. hello, arrow.",
"intTensor" : [ 7756, 9549, 1094, 9808, 4959, 3831, 3926, 6578, 1870, 1741 ],
"floatTensor" : [ 0.6804766, 0.30136853, 0.17394465, 0.44770062, 0.20275897, 0.32762378, 0.45966738, 0.30405098, 0.62053126, 0.7037923 ],
"stringTensor" : [ "come", "on", "united" ],
"intTensor2" : [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ],
"floatTensor2" : [ [ [ 0.2, 0.3 ], [ 0.5, 0.6 ] ], [ [ 0.2, 0.3 ], [ 0.5, 0.6 ] ] ],
"stringTensor2" : [ [ [ [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ] ], [ [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ] ] ], [ [ [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ] ], [ [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ], [ "come", "on", "united" ] ] ] ]
}]
}' \
-X POST http://host:port/predict
Another request example for composition of sparse and dense tensors.
curl -d \
'{
"instances" : [ {
"sparseTensor" : {
"shape" : [ 100, 10000, 10 ],
"data" : [ 0.2, 0.5, 3.45, 6.78 ],
"indices" : [ [ 1, 1, 1 ], [ 2, 2, 2 ], [ 3, 3, 3 ], [ 4, 4, 4 ] ]
},
"intTensor2" : [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
}]
}' \
-X POST http://host:port/predict
Metrics API
URL
GET http://host:port/metrics
Response example:
[
{
name: "zoo.serving.redis.get",
count: 810,
meanRate: 12.627772820651845,
min: 0,
max: 25,
mean: 0.9687099303718213,
median: 0.928579,
stdDev: 0.8150031623593447,
_75thPercentile: 1.000047,
_95thPercentile: 1.141443,
_98thPercentile: 1.268665,
_99thPercentile: 1.608387,
_999thPercentile: 25.874584
}
]
Optional Operations
Update Model or Configurations
To update your model, you could replace your model file in your model directory, and restart Cluster Serving by cluster-serving-restart
. Note that you could also change your configurations in config.yaml
and restart serving.
Logs and Visualization
Logs
To see log, please refer to Flink UI localhost:8081
by default.
Visualization
To visualize Cluster Serving performance, go to your flink job UI, default localhost:8081
, and go to Cluster Serving job -> metrics. Add numRecordsOut
to see total record number and numRecordsOutPerSecond
to see throughput.
See example of visualization:
Others
Transfer Local Code to Cluster Serving
If you have existed local application, we provide some example for you to transfer them to Cluster Serving application.
We recommend Keras tranformation guide. For Tensorflow v1 users, we also provide Tensorflow v1 transformation guide.
Debug Guide
If you follow this programming guide but Cluster Serving does not work, we provide a Debug Guide for you to figure out the problem step by step.
Contribution Guide
We are glad if you are willing to contribute to Cluster Serving, refer to Contribution Guide for details.


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