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F

featNames - Variable in class jncc20.Jncc
Names of input features
featureNames - Variable in class jncc20.ArffParser
Names of input features
featureNames - Variable in class jncc20.Jncc.ResultsReporter
Names of input features
featureSet - Variable in class jncc20.NaiveClassifier
Array of Feature objects, that represents the feature set of the classifier
FeatureValue - Variable in class jncc20.MdlDiscretizer.Pair
 
findMinimizingValue(int, int, int, int, double, double) - Method in class jncc20.NaiveCredalClassifier
Given a sub-partion (xmin,xmax) of[0,s], returns the value of feature FeatureIdx, which minimizes the ratio (lowercount(feature,c1)/(uppercount(feature,c2)+x)) in the interval.
findNonMarInCurrentDataset() - Method in class jncc20.Jncc
Prepares the NonMarInCurrentDataset data member.
findPartitionPoints(int, int, ArrayList<Integer>) - Method in class jncc20.NaiveCredalClassifier
If there are missing data in the NonMar part of the units to be classified, this function identifies the intervals in which the range [0,s] has to be sub-partitioned.
findZeroCIR(double, double, int, int, ArrayList<Integer>, ArrayList<Integer>, ArrayList<Integer>, ArrayList<Integer>, ArrayList<Integer>, ArrayList<Integer>) - Method in class jncc20.NaiveCredalClassifier
Numerical approximation of the min of Ln(Hx) via Newton-Raphson method.
foldsSize - Variable in class jncc20.Jncc
How many instances are in each fold
frequencies - 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.
frequency - Variable in class jncc20.NaiveClassifier.OutputClass
 

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