MOA 12.03
Real Time Analytics for Data Streams
moa.tasks.LearnModel Class Reference

Task for learning a model without any evaluation. More...

Inheritance diagram for moa.tasks.LearnModel:
Collaboration diagram for moa.tasks.LearnModel:

List of all members.

Public Member Functions

String getPurposeString ()
 Gets the purpose of this object.
 LearnModel ()
 LearnModel (Classifier learner, InstanceStream stream, int maxInstances, int numPasses)
Class<?> getTaskResultType ()
 Gets the result type of this task.
Object doMainTask (TaskMonitor monitor, ObjectRepository repository)
 This method performs this task.

Public Attributes

ClassOption learnerOption
ClassOption streamOption
IntOption maxInstancesOption
IntOption numPassesOption
IntOption memCheckFrequencyOption

Detailed Description

Task for learning a model without any evaluation.

Author:
Richard Kirkby (rkirkby@cs.waikato.ac.nz)
Version:
Revision:
7

Definition at line 34 of file LearnModel.java.


Constructor & Destructor Documentation

moa.tasks.LearnModel.LearnModel ( )

Definition at line 63 of file LearnModel.java.

moa.tasks.LearnModel.LearnModel ( Classifier  learner,
InstanceStream  stream,
int  maxInstances,
int  numPasses 
)

Definition at line 66 of file LearnModel.java.

Here is the call graph for this function:


Member Function Documentation

Object moa.tasks.LearnModel.doMainTask ( TaskMonitor  monitor,
ObjectRepository  repository 
) [virtual]

This method performs this task.

AbstractTask implements doTask, that uses doTaskImpl. MainTask implements doTaskImpl using doMainTask so its extensions only need to implement doMainTask.

Parameters:
monitorthe TaskMonitor to use
repositorythe ObjectRepository to use
Returns:
an object with the result of this task

Implements moa.tasks.MainTask.

Definition at line 80 of file LearnModel.java.

Here is the call graph for this function:

String moa.tasks.LearnModel.getPurposeString ( )

Gets the purpose of this object.

Returns:
the string with the purpose of this object

Reimplemented from moa.options.AbstractOptionHandler.

Definition at line 37 of file LearnModel.java.

Class<?> moa.tasks.LearnModel.getTaskResultType ( )

Gets the result type of this task.

Tasks can return LearningCurve, LearningEvaluation, Classifier, String, Instances..

Returns:
a class object of the result of this task

Implements moa.tasks.Task.

Definition at line 75 of file LearnModel.java.


Member Data Documentation

Initial value:
 new ClassOption("learner", 'l',
            "Classifier to train.", Classifier.class, "bayes.NaiveBayes")

Definition at line 43 of file LearnModel.java.

Referenced by moa.tasks.LearnModel.doMainTask(), and moa.tasks.LearnModel.LearnModel().

Initial value:
 new IntOption("maxInstances", 'm',
            "Maximum number of instances to train on per pass over the data.",
            10000000, 0, Integer.MAX_VALUE)

Definition at line 50 of file LearnModel.java.

Referenced by moa.tasks.LearnModel.doMainTask(), and moa.tasks.LearnModel.LearnModel().

Initial value:
 new IntOption(
            "memCheckFrequency", 'q',
            "How many instances between memory bound checks.", 100000, 0,
            Integer.MAX_VALUE)

Definition at line 58 of file LearnModel.java.

Initial value:
 new IntOption("numPasses", 'p',
            "The number of passes to do over the data.", 1, 1,
            Integer.MAX_VALUE)

Definition at line 54 of file LearnModel.java.

Referenced by moa.tasks.LearnModel.doMainTask(), and moa.tasks.LearnModel.LearnModel().

Initial value:
 new ClassOption("stream", 's',
            "Stream to learn from.", InstanceStream.class,
            "generators.RandomTreeGenerator")

Definition at line 46 of file LearnModel.java.

Referenced by moa.tasks.LearnModel.doMainTask(), and moa.tasks.LearnModel.LearnModel().


The documentation for this class was generated from the following file:
 All Classes Namespaces Files Functions Variables Enumerations