CategoricalEntailmentEnsembleClassifierTrain Method

public static CategoricalEntailmentEnsembleClassifier Train(
	CategoricalDataSet dataSet,
	IndexCollection featureVariableIndexes,
	int responseVariableIndex,
	int numberOfTrainedCategoricalEntailments,
	bool allowEntailmentPartialTruthValues,
	bool trainSequentially
)

Public Shared Function Train ( 
	dataSet As CategoricalDataSet,
	featureVariableIndexes As IndexCollection,
	responseVariableIndex As Integer,
	numberOfTrainedCategoricalEntailments As Integer,
	allowEntailmentPartialTruthValues As Boolean,
	trainSequentially As Boolean
) As CategoricalEntailmentEnsembleClassifier

public:
static CategoricalEntailmentEnsembleClassifier^ Train(
	CategoricalDataSet^ dataSet, 
	IndexCollection^ featureVariableIndexes, 
	int responseVariableIndex, 
	int numberOfTrainedCategoricalEntailments, 
	bool allowEntailmentPartialTruthValues, 
	bool trainSequentially
)

static member Train : 
        dataSet : CategoricalDataSet * 
        featureVariableIndexes : IndexCollection * 
        responseVariableIndex : int * 
        numberOfTrainedCategoricalEntailments : int * 
        allowEntailmentPartialTruthValues : bool * 
        trainSequentially : bool -> CategoricalEntailmentEnsembleClassifier 

Parameters

dataSet  CategoricalDataSet

The categorical data set containing information about the available feature and response variables.

featureVariableIndexes  IndexCollection

The zero-based indexes of the columns in dataSet containing observations about the feature variables on which premises must be defined.

responseVariableIndex  Int32

The zero-based index of the column in dataSet containing observations about the response variable.

numberOfTrainedCategoricalEntailments  Int32

The number of categorical entailments to be trained.

allowEntailmentPartialTruthValues  Boolean

If set to true signals that the truth value of a categorical entailment must be equal to the homogeneity of the probability distribution from which its conclusion has been drawn. Otherwise, the truth value is unity.

trainSequentially  Boolean

If set to true signals that the ensemble is trained sequentially, i.e. it starts as an empty collection, and new categorical entailments are added through a step-by-step procedure to the trained ensemble, by selecting, at each step, the entailment that better improves the system's performance of the current ensemble. Otherwise, the categorical entailments are trained simultaneously.

Return Value

Reference