weka.clusterers

Class ScikitLearnClusterer

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.ScikitLearnClusterer

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.clusterers.Clusterer, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler

public class ScikitLearnClusterer
extends weka.clusterers.AbstractClusterer
implements weka.core.BatchPredictor

Wrapper clusterer fro clusterers implemented in the scikit-learn Python package.

Version:

$Revision: 15657 $

Author:

Mark Hall (mhall{[at]}pentaho{[dot]}com)

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ScikitLearnClusterer.Clusterer Holds info on the different learners available

Field Summary

Fields

Modifier and Type	Field and Description
static weka.core.Tag[]	TAGS_LEARNER The tags for the GUI drop-down for learner selection

Constructor Summary

Constructors

Constructor and Description
ScikitLearnClusterer()

Method Summary

Modifier and Type	Method and Description
void	buildClusterer(weka.core.Instances data) Build the clusterer
double[]	distributionForInstance(weka.core.Instance inst) Return the predicted cluster memberships for the supplied instance
double[][]	distributionsForInstances(weka.core.Instances insts) Return the predicted cluster memberships for the supplied instances
java.lang.String	getBatchSize()
weka.core.Capabilities	getCapabilities() Get the capabilities of this learner
weka.core.SelectedTag	getClusterer()
boolean	getContinueOnSysErr() Get whether to try and continue after seeing output on the sys error stream.
java.lang.String	getLearnerOpts() Get the parameters to pass to the scikit-learn scheme
java.lang.String	getPythonCommand() Get the python command to use.
java.lang.String	getPythonPath() Get optional entries to prepend to the PATH so that python can execute correctly.
java.lang.String	getServerID() Get an optional server name by which to identify the python server to use.
java.lang.String	globalInfo() Global help info
boolean	implementsMoreEfficientBatchPrediction() Return true as we send entire test sets over to python for prediction
static void	main(java.lang.String[] args) Main method for testing this class
int	numberOfClusters()
void	setBatchSize(java.lang.String size)
void	setClusterer(weka.core.SelectedTag learner) Set the scikit-learn clustering scheme to use
void	setContinueOnSysErr(boolean c) Set whether to try and continue after seeing output on the sys error stream.
void	setLearnerOpts(java.lang.String opts) Set the parameters to pass to the scikit-learn scheme
void	setPythonCommand(java.lang.String pyCommand) Set the python command to use.
void	setPythonPath(java.lang.String pythonPath) Set optional entries to prepend to the PATH so that python can execute correctly.
void	setServerID(java.lang.String serverID) Set an optional server name by which to identify the python server to use.
java.lang.String	toString() Get a textual description of this scheme

Methods inherited from class weka.clusterers.AbstractClusterer

clusterInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, getOptions, getRevision, listOptions, makeCopies, makeCopy, postExecution, preExecution, run, runClusterer, setDebug, setDoNotCheckCapabilities, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler

makeCopy

Field Detail

TAGS_LEARNER

public static final weka.core.Tag[] TAGS_LEARNER

The tags for the GUI drop-down for learner selection

Constructor Detail

ScikitLearnClusterer

public ScikitLearnClusterer()

Method Detail

globalInfo

public java.lang.String globalInfo()

Global help info

Returns:

the global help info for this scheme

getCapabilities

public weka.core.Capabilities getCapabilities()

Get the capabilities of this learner

Specified by:

getCapabilities in interface weka.clusterers.Clusterer

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class weka.clusterers.AbstractClusterer

Returns:

the capabilities of this scheme

getClusterer

@OptionMetadata(displayName="Scikit-learn clusterer",
                description="Scikit-learn clusterer to use.\nAvailable clusterers:\nAffinityPropagation, KMeans, DBSCAN",
                commandLineParamName="clusterer",
                commandLineParamSynopsis="-clusterer <clusterer name>",
                displayOrder=1)
public weka.core.SelectedTag getClusterer()

setClusterer

public void setClusterer(weka.core.SelectedTag learner)

Set the scikit-learn clustering scheme to use

Parameters:

learner - the scikit-learn clustering scheme to use

getLearnerOpts

@OptionMetadata(displayName="Learner parameters",
                description="learner parameters to use",
                displayOrder=2,
                commandLineParamName="parameters",
                commandLineParamSynopsis="-parameters <comma-separated list of name=value pairs>")
public java.lang.String getLearnerOpts()

Get the parameters to pass to the scikit-learn scheme

Returns:

the parameters to use

setLearnerOpts

public void setLearnerOpts(java.lang.String opts)

Set the parameters to pass to the scikit-learn scheme

Parameters:

opts - the parameters to use

setBatchSize

public void setBatchSize(java.lang.String size)

Specified by:

setBatchSize in interface weka.core.BatchPredictor

getBatchSize

@OptionMetadata(displayName="Batch size",
                description="The preferred number of instances to transfer into python for prediction\n(if operatingin batch prediction mode). More or fewer instances than this will be accepted.",
                commandLineParamName="batch",
                commandLineParamSynopsis="-batch <batch size>",
                displayOrder=4)
public java.lang.String getBatchSize()

Specified by:

getBatchSize in interface weka.core.BatchPredictor

implementsMoreEfficientBatchPrediction

public boolean implementsMoreEfficientBatchPrediction()

Return true as we send entire test sets over to python for prediction

Specified by:

implementsMoreEfficientBatchPrediction in interface weka.core.BatchPredictor

Returns:

true

setContinueOnSysErr

public void setContinueOnSysErr(boolean c)

Set whether to try and continue after seeing output on the sys error stream.

Parameters:

c - true if we should try to continue after seeing output on the sys error stream

getContinueOnSysErr

@OptionMetadata(displayName="Try to continue after sys err output from script",
                description="Try to continue after sys err output from script.\nSome schemesreport warnings to the system error stream.",
                displayOrder=5,
                commandLineParamName="continue-on-err",
                commandLineParamSynopsis="-continue-on-err",
                commandLineParamIsFlag=true)
public boolean getContinueOnSysErr()

Get whether to try and continue after seeing output on the sys error stream.

Returns:

true if we should try to continue after seeing output on the sys error stream

setPythonCommand

public void setPythonCommand(java.lang.String pyCommand)

Set the python command to use. Empty string or "default" indicate that the python present in the PATH should be used.

Parameters:

pyCommand - the path to the python executable (or empty string/"default" to use python in the PATH)

getPythonCommand

@OptionMetadata(displayName="Python command ",
                description="Path to python executable (\'default\' to use python in the PATH)",
                commandLineParamName="py-command",
                commandLineParamSynopsis="-py-command <path to python executable>",
                displayOrder=7)
public java.lang.String getPythonCommand()

Get the python command to use. Empty string or "default" indicate that the python present in the PATH should be used.

Returns:

the path to the python executable (or empty string/"default" to use python in the PATH)

setPythonPath

public void setPythonPath(java.lang.String pythonPath)

Set optional entries to prepend to the PATH so that python can execute correctly. Only applies when not using a default python.

Parameters:

pythonPath - additional entries to prepend to the PATH

getPythonPath

@OptionMetadata(displayName="Python path",
                description="Optional elements to prepend to the PATH so that python can execute correctly (\'default\' to use PATH as-is)",
                commandLineParamName="py-path",
                commandLineParamSynopsis="-py-path <path>",
                displayOrder=8)
public java.lang.String getPythonPath()

Get optional entries to prepend to the PATH so that python can execute correctly. Only applies when not using a default python.

Returns:

additional entries to prepend to the PATH

setServerID

public void setServerID(java.lang.String serverID)

Set an optional server name by which to identify the python server to use. Can be used share a given server amongst selected instances or reserve a server specifically for this classifier. Python command + server name uniquely identifies the server to use.

Parameters:

serverID - the name of the server to use (or none for no specific server name).

getServerID

@OptionMetadata(displayName="Server name/ID",
                description="Optional name to identify this server, can be used to share a given server instance - default = \'none\' (i.e. no server name)",
                commandLineParamName="server-name",
                commandLineParamSynopsis="-server-name <server name | none>",
                displayOrder=9)
public java.lang.String getServerID()

Get an optional server name by which to identify the python server to use. Can be used share a given server amongst selected instances or reserve a server specifically for this classifier. Python command + server name uniquely identifies the server to use.

Returns:

the name of the server to use (or none) for no specific server name.

buildClusterer

public void buildClusterer(weka.core.Instances data)
                    throws java.lang.Exception

Build the clusterer

Specified by:

buildClusterer in interface weka.clusterers.Clusterer

Specified by:

buildClusterer in class weka.clusterers.AbstractClusterer

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if a problem occurs

numberOfClusters

public int numberOfClusters()
                     throws java.lang.Exception

Specified by:

numberOfClusters in interface weka.clusterers.Clusterer

Specified by:

numberOfClusters in class weka.clusterers.AbstractClusterer

Throws:

java.lang.Exception

distributionsForInstances

public double[][] distributionsForInstances(weka.core.Instances insts)
                                     throws java.lang.Exception

Return the predicted cluster memberships for the supplied instances

Specified by:

distributionsForInstances in interface weka.core.BatchPredictor

Parameters:

insts - the instances to get predictions for

Returns:

the predicted cluster memberships for the supplied instances

Throws:

java.lang.Exception - if a problem occurs

distributionForInstance

public double[] distributionForInstance(weka.core.Instance inst)
                                 throws java.lang.Exception

Return the predicted cluster memberships for the supplied instance

Specified by:

distributionForInstance in interface weka.clusterers.Clusterer

Overrides:

distributionForInstance in class weka.clusterers.AbstractClusterer

Parameters:

inst - the instance to be classified

Returns:

the predicted cluster memberships

Throws:

java.lang.Exception - if a problem occurs

toString

public java.lang.String toString()

Get a textual description of this scheme

Overrides:

toString in class java.lang.Object

Returns:

a textual description of this scheme

main

public static void main(java.lang.String[] args)

Main method for testing this class

Parameters:

args - command line args