magpie.data.utilities.splitters

Class PredictedClassIntervalSplitter

java.lang.Object

magpie.data.utilities.splitters.BaseDatasetSplitter

magpie.data.utilities.splitters.PredictedClassIntervalSplitter

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Commandable, Options, Printable

public class PredictedClassIntervalSplitter
extends BaseDatasetSplitter

Splits data based on whether the class variable is predicted to be within certain intervals. Partitioning is based on an internal classifier, which is trained using the train(magpie.data.Dataset) operation.

Usage: $<classifier> <interval edges...>
classifier: AbstractClassifier used to predict class interval.
interval edges...: Values that define the edges of intervals. Edges will extend from (-Inf,Value1], (Value1,Value2], (ValueN, Inf).

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PredictedClassIntervalSplitter() Create a new instances that uses ZeroR to predict interval.

Method Summary

Modifier and Type	Method and Description
PredictedClassIntervalSplitter	clone()
java.util.List<java.lang.String>	getSplitNames() Get the names of the splits this splitter creates
protected java.util.List<java.lang.String>	getSplitterDetails(boolean htmlFormat) Get details of splitter.
int[]	label(Dataset D) Given a dataset, determine which subset each entry should belong to.
java.lang.String	printUsage() Print out required format for options.
void	setClassifier(BaseModel Clfr) Define the classifier used to predict on which interval a class variable most likely lies.
void	setEdges(double[] edges) Define edges describing different values of the class variable on which entries are partitioned.
void	setOptions(java.util.List<java.lang.Object> Options) Set any options for this object.
void	train(Dataset TrainingSet) Train a dataset splitter, if necessary

Methods inherited from class magpie.data.utilities.splitters.BaseDatasetSplitter

about, printCommand, printDescription, runCommand, split, split

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PredictedClassIntervalSplitter

public PredictedClassIntervalSplitter()
                               throws java.lang.Exception

Create a new instances that uses ZeroR to predict interval.

Throws:

java.lang.Exception

Method Detail

clone

public PredictedClassIntervalSplitter clone()

Overrides:

clone in class BaseDatasetSplitter

setOptions

public void setOptions(java.util.List<java.lang.Object> Options)
                throws java.lang.Exception

Description copied from interface: Options

Set any options for this object. If parsing the options fails, return an Exception with the usage as its message.

Parameters:

Options - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

printUsage

public java.lang.String printUsage()

Description copied from interface: Options

Print out required format for options. For consistency, should start with "Usage: ".

Returns:

Usage for this function

setClassifier

public void setClassifier(BaseModel Clfr)

Define the classifier used to predict on which interval a class variable most likely lies.

Parameters:

Clfr - Classifier will that will be used

setEdges

public void setEdges(double[] edges)

Define edges describing different values of the class variable on which entries are partitioned. Edges are defined by: (-Inf, edge[0]], (edge[0], edge[1]], ..., (edge[N], Inf)

Parameters:

edges - Edges of class intervals

train

public void train(Dataset TrainingSet)

Description copied from class: BaseDatasetSplitter

Train a dataset splitter, if necessary

Specified by:

train in class BaseDatasetSplitter

Parameters:

TrainingSet - Dataset to use for training

label

public int[] label(Dataset D)

Description copied from class: BaseDatasetSplitter

Given a dataset, determine which subset each entry should belong to. Please ensure that D remains unaltered (clone if you must)

Specified by:

label in class BaseDatasetSplitter

Parameters:

D - Dataset to be labeled

Returns:

A list of nonnegative integers marking which subset to split each entry into

getSplitterDetails

protected java.util.List<java.lang.String> getSplitterDetails(boolean htmlFormat)

Description copied from class: BaseDatasetSplitter

Get details of splitter. Returns a list of options that can be set by the user. Used with BaseDatasetSplitter.printDescription(boolean).

Specified by:

getSplitterDetails in class BaseDatasetSplitter

Parameters:

htmlFormat - Whether to format results with HTML

Returns:

List of options describing the model

getSplitNames

public java.util.List<java.lang.String> getSplitNames()

Description copied from class: BaseDatasetSplitter

Get the names of the splits this splitter creates

Specified by:

getSplitNames in class BaseDatasetSplitter

Returns:

Names of each group