CategoricalEntailmentEnsembleClassifierAddTrained Method

public void AddTrained(
	CategoricalDataSet dataSet,
	IndexCollection featureVariableIndexes,
	int responseVariableIndex,
	int numberOfTrainedCategoricalEntailments,
	bool allowEntailmentPartialTruthValues,
	bool trainSequentially
)

Public Sub AddTrained ( 
	dataSet As CategoricalDataSet,
	featureVariableIndexes As IndexCollection,
	responseVariableIndex As Integer,
	numberOfTrainedCategoricalEntailments As Integer,
	allowEntailmentPartialTruthValues As Boolean,
	trainSequentially As Boolean
)

public:
void AddTrained(
	CategoricalDataSet^ dataSet, 
	IndexCollection^ featureVariableIndexes, 
	int responseVariableIndex, 
	int numberOfTrainedCategoricalEntailments, 
	bool allowEntailmentPartialTruthValues, 
	bool trainSequentially
)

member AddTrained : 
        dataSet : CategoricalDataSet * 
        featureVariableIndexes : IndexCollection * 
        responseVariableIndex : int * 
        numberOfTrainedCategoricalEntailments : int * 
        allowEntailmentPartialTruthValues : bool * 
        trainSequentially : bool -> unit 

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

The entailments to be trained are added to the Entailments to optimally enlarge such collection by the specified numberOfTrainedCategoricalEntailments.

it is expected that featureVariableIndexes has the same count of the FeatureVariables of this instance, and that the -th position of featureVariableIndexes is the index of the column that, in dataSet, contains observations about the -th feature variable of the classifier. Furthermore, responseVariableIndex must be the index of the column where, in dataSet, are stored observations about the ResponseVariable of this instance.

Reference