org.android.activityminer.pmml.model.knn
Class NearestNeighborModel

java.lang.Object
  org.android.activityminer.pmml.model.knn.NearestNeighborModel

All Implemented Interfaces:

ModelElement

public class NearestNeighborModel
extends Object
implements ModelElement

A simple nearest neighbor model representation (without extensions, model statistics, model explanation, targets, local transformations and model verification elements)

Field Summary

private String	algorithmName Can be any string describing the algorithm that was used while creating the k-NN model.
private CatScoringMethod	categoricalScoringMethod Specify the scoring (or combining) method for categorical target values of K neighbors
private ComparisonMeasure	comparisonMeasure The comparison measure
private ContScoringMethod	continuousScoringMethod Specify the scoring (or combining) method for continuous target values of K neighbors
private MiningFunctionType	functionName Could be either "classification" or "regression" depending on the target variable(s).
private String	instanceIdVariable Contains the instance ID variable name and so refers to the name of a field in InstanceFields.
private boolean	isScorable This attribute indicates if the model is valid for scoring.
private KNNInputs	knnInputs The knn inputs
private LocalTransformations	localTransformations The local transformations
private MiningSchema	miningSchema The mining schema
private String	modelName A unique identifier specifying the name of the k-NN model
private int	numberOfNeighbors instanceFields Specifies K, the number of desired neighbors.
private Output	output The output
private double	threshold Defines a very small positive number to be used for "weighted" scoring methods to avoid numerical problems when distance or similarity measure is zero.
private TrainingInstances	trainingInstances The training instances

Constructor Summary

NearestNeighborModel()

Method Summary

String	getAlgorithmName() Getter for the algorithmName
CatScoringMethod	getCategoricalScoringMethod() Getter for the categoricalScoringMethod
ComparisonMeasure	getComparisonMeasure() Getter for the comparisonMeasure
ContScoringMethod	getContinuousScoringMethod() Getter for the continuousScoringMethod
MiningFunctionType	getFunctionName() Getter for the functionName
String	getInstanceIdVariable() Getter for the instanceIdVariable
String	getIsScorableValue() Getter for the isScorable XML attribute value
KNNInputs	getKnnInputs() Getter for the knnInputs
LocalTransformations	getLocalTransformations() Getter for the localTransformations
MiningSchema	getMiningSchema() Getter for the miningSchema
String	getModelName() Getter for the modelName
int	getNumberOfNeighbors() Getter for the numberOfNeighbors
Output	getOutput() Getter for the output
double	getThreshold() Getter for the threshold
TrainingInstances	getTrainingInstances() Getter for the trainingInstances
boolean	isScorable() Getter for the isScorable
void	setAlgorithmName(String algorithmName) Setter for the algorithmName
void	setCategoricalScoringMethod(CatScoringMethod categoricalScoringMethod) Setter for the categoricalScoringMethod
void	setComparisonMeasure(ComparisonMeasure comparisonMeasure) Setter for the comparisonMeasure
void	setContinuousScoringMethod(ContScoringMethod continuousScoringMethod) Setter for the continuousScoringMethod
void	setFunctionName(MiningFunctionType functionName) Setter for the functionName
void	setInstanceIdVariable(String instanceIdVariable) Setter for the instanceIdVariable
void	setIsScorableValue(String isCyclic) Setter for the isScorable XML attribute value
void	setKnnInputs(KNNInputs knnInputs) Setter for the knnInputs
void	setLocalTransformations(LocalTransformations localTransformations) Setter for the localTransformations
void	setMiningSchema(MiningSchema miningSchema) Setter for the miningSchema
void	setModelName(String modelName) Setter for the modelName
void	setNumberOfNeighbors(int numberOfNeighbors) Setter for the numberOfNeighbors
void	setOutput(Output output) Setter for the output
void	setScorable(boolean isScorable) Setter for the isScorable
void	setThreshold(double threshold) Setter for the threshold
void	setTrainingInstances(TrainingInstances trainingInstances) Setter for the trainingInstances

Methods inherited from class java.lang.Object

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

Field Detail

modelName

private String modelName

A unique identifier specifying the name of the k-NN model

functionName

private MiningFunctionType functionName

Could be either "classification" or "regression" depending on the target variable(s). If the model contains categorical and continuous targets, this attribute should be "mixed". In case no targets are present then it should be "clustering".

algorithmName

private String algorithmName

Can be any string describing the algorithm that was used while creating the k-NN model.

numberOfNeighbors

private int numberOfNeighbors

instanceFields Specifies K, the number of desired neighbors.

continuousScoringMethod

private ContScoringMethod continuousScoringMethod

Specify the scoring (or combining) method for continuous target values of K neighbors

categoricalScoringMethod

private CatScoringMethod categoricalScoringMethod

Specify the scoring (or combining) method for categorical target values of K neighbors

instanceIdVariable

private String instanceIdVariable

Contains the instance ID variable name and so refers to the name of a field in InstanceFields. Required if the model has no targets, optional otherwise.

threshold

private double threshold

Defines a very small positive number to be used for "weighted" scoring methods to avoid numerical problems when distance or similarity measure is zero.

isScorable

private boolean isScorable

This attribute indicates if the model is valid for scoring. If this attribute is true or if it is missing, then the model should be processed normally. However, if the attribute is false, then the model producer has indicated that this model is intended for information purposes only and should not be used to generate results.

miningSchema

private MiningSchema miningSchema

The mining schema

trainingInstances

private TrainingInstances trainingInstances

The training instances

comparisonMeasure

private ComparisonMeasure comparisonMeasure

The comparison measure

knnInputs

private KNNInputs knnInputs

The knn inputs

output

private Output output

The output

localTransformations

private LocalTransformations localTransformations

The local transformations

Constructor Detail

NearestNeighborModel

public NearestNeighborModel()

Method Detail

setMiningSchema

public void setMiningSchema(MiningSchema miningSchema)

Description copied from interface: ModelElement

Setter for the miningSchema

Specified by:

setMiningSchema in interface ModelElement

Parameters:

miningSchema - the miningSchema to set

getMiningSchema

public MiningSchema getMiningSchema()

Description copied from interface: ModelElement

Getter for the miningSchema

Specified by:

getMiningSchema in interface ModelElement

Returns:

the miningSchema

setModelName

public void setModelName(String modelName)

Setter for the modelName

Parameters:

modelName - the modelName to set

getModelName

public String getModelName()

Getter for the modelName

Returns:

the modelName

setFunctionName

public void setFunctionName(MiningFunctionType functionName)

Setter for the functionName

Parameters:

functionName - the functionName to set

getFunctionName

public MiningFunctionType getFunctionName()

Getter for the functionName

Returns:

the functionName

setAlgorithmName

public void setAlgorithmName(String algorithmName)

Setter for the algorithmName

Parameters:

algorithmName - the algorithmName to set

getAlgorithmName

public String getAlgorithmName()

Getter for the algorithmName

Returns:

the algorithmName

setNumberOfNeighbors

public void setNumberOfNeighbors(int numberOfNeighbors)

Setter for the numberOfNeighbors

Parameters:

numberOfNeighbors - the numberOfNeighbors to set

getNumberOfNeighbors

public int getNumberOfNeighbors()

Getter for the numberOfNeighbors

Returns:

the numberOfNeighbors

setContinuousScoringMethod

public void setContinuousScoringMethod(ContScoringMethod continuousScoringMethod)

Setter for the continuousScoringMethod

Parameters:

continuousScoringMethod - the continuousScoringMethod to set

getContinuousScoringMethod

public ContScoringMethod getContinuousScoringMethod()

Getter for the continuousScoringMethod

Returns:

the continuousScoringMethod

setCategoricalScoringMethod

public void setCategoricalScoringMethod(CatScoringMethod categoricalScoringMethod)

Setter for the categoricalScoringMethod

Parameters:

categoricalScoringMethod - the categoricalScoringMethod to set

getCategoricalScoringMethod

public CatScoringMethod getCategoricalScoringMethod()

Getter for the categoricalScoringMethod

Returns:

the categoricalScoringMethod

getInstanceIdVariable

public String getInstanceIdVariable()

Getter for the instanceIdVariable

Returns:

the instanceIdVariable

getThreshold

public double getThreshold()

Getter for the threshold

Returns:

the threshold

setInstanceIdVariable

public void setInstanceIdVariable(String instanceIdVariable)

Setter for the instanceIdVariable

Parameters:

instanceIdVariable - the instanceIdVariable to set

setThreshold

public void setThreshold(double threshold)

Setter for the threshold

Parameters:

threshold - the threshold to set

setScorable

public void setScorable(boolean isScorable)

Setter for the isScorable

Parameters:

isScorable - the isScorable to set

isScorable

public boolean isScorable()

Getter for the isScorable

Returns:

the isScorable

setIsScorableValue

public void setIsScorableValue(String isCyclic)

Setter for the isScorable XML attribute value

Parameters:

isCyclic - the isScorable XML attribute value to set

getIsScorableValue

public String getIsScorableValue()

Getter for the isScorable XML attribute value

Returns:

the isScorable XML attribute value

setOutput

public void setOutput(Output output)

Description copied from interface: ModelElement

Setter for the output

Specified by:

setOutput in interface ModelElement

Parameters:

output - the output to set

getOutput

public Output getOutput()

Description copied from interface: ModelElement

Getter for the output

Specified by:

getOutput in interface ModelElement

Returns:

the output

setTrainingInstances

public void setTrainingInstances(TrainingInstances trainingInstances)

Setter for the trainingInstances

Parameters:

trainingInstances - the trainingInstances to set

getTrainingInstances

public TrainingInstances getTrainingInstances()

Getter for the trainingInstances

Returns:

the trainingInstances

setComparisonMeasure

public void setComparisonMeasure(ComparisonMeasure comparisonMeasure)

Setter for the comparisonMeasure

Parameters:

comparisonMeasure - the comparisonMeasure to set

getComparisonMeasure

public ComparisonMeasure getComparisonMeasure()

Getter for the comparisonMeasure

Returns:

the comparisonMeasure

setKnnInputs

public void setKnnInputs(KNNInputs knnInputs)

Setter for the knnInputs

Parameters:

knnInputs - the knnInputs to set

getKnnInputs

public KNNInputs getKnnInputs()

Getter for the knnInputs

Returns:

the knnInputs

getLocalTransformations

public LocalTransformations getLocalTransformations()

Getter for the localTransformations

Returns:

the localTransformations

setLocalTransformations

public void setLocalTransformations(LocalTransformations localTransformations)

Setter for the localTransformations

Parameters:

localTransformations - the localTransformations to set