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C

categoryNames - Variable in class jncc20.Jncc
Matrix of String with rows of different lenght; stores the name of the categories (each row corresponds to a different feature); meaningful for categorical features only.
checkArgs(String[]) - Static method in class jncc20.Jncc
Sanity-check of the parameters supplied by the user
checkCredalDominanceCIR(int, int, int[], double, double) - Method in class jncc20.NaiveCredalClassifier2
Computes the CIR test of dominance between class c1 and c2 (if the returned value is >1, c1 dominates c2)
classifyInstance(int[], int) - Method in class jncc20.NaiveBayes
Classify a single instance, writing the computed probabilities at position InstanceIdx of probabilities, and the predicted class at position InstanceIdx of predictions
classifyInstance(int[]) - Method in class jncc20.NaiveCredalClassifier2
Classifies a single instance, returning the list of predicted classes
classifyInstances(ArrayList<int[]>) - Method in class jncc20.NaiveBayes
Classifies all the instances of the supplied TestingSet, writing the results of the computation into EstimatedProbabilities and PredictedInstances
classifyInstances(ArrayList<int[]>) - Method in class jncc20.NaiveClassifier
Abstract function
classifyInstances(ArrayList<int[]>) - Method in class jncc20.NaiveCredalClassifier2
Classify all the instances of the supplied TestingSet; stores the predictions into CredalPredictedInstances
classNames - Variable in class jncc20.Jncc
Names of the output classes.
ClassValue - Variable in class jncc20.MdlDiscretizer.Pair
 
compareTo(Object) - Method in class jncc20.MdlDiscretizer.Pair
Compares two Pair, ordering the on the basis of the feature value.
compareTo(Object) - Method in class jncc20.NaiveCredalClassifier2.PartitionPoint
 
computeDeriv2LnHxCIR(double) - Method in class jncc20.NaiveCredalClassifier2
Computes the second derivative of Ln(Hx) (see Corani and Zaffalon, 2007)
computeDerivLnHxCIR(double) - Method in class jncc20.NaiveCredalClassifier2
Computes the derivative of Ln(Hx) (see Corani and Zaffalon, 2007)
computeEntropy(int, int) - Method in class jncc20.MdlDiscretizer
Computes the entropy of the partion of pairVector comprised between the indexes lowerBound and upperBound
computeHxCIR(double) - Method in class jncc20.NaiveCredalClassifier2
Computes Hx for a given value of x, alpha, beta ecc.
computePossibleCutPoints() - Method in class jncc20.MdlDiscretizer
Identifies the feature values that can constitute possible cutPoints (i.e., possible discretization intervals)
conditionalFreq - Variable in class jncc20.NaiveClassifier.Feature
Counts that correspond to counts-after-dropping-missing for MarFeatures, bivariate count: frequency are computed for each output class and for each class of the feature.
crossingX - Variable in class jncc20.NaiveCredalClassifier2.PartitionPoint
Value of the crossing point
currentCvFold - Variable in class jncc20.Jncc
 
cvFoldsIdx - Variable in class jncc20.Jncc
Indexes for cross validation: in which fold each row of rawDataset falls

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