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P

pairVector - Variable in class jncc20.MdlDiscretizer
Vector of feature/class pairs
parseArffFile() - Method in class jncc20.Jncc
Scans the main Arff file.
parseArffTestingFile(boolean) - Method in class jncc20.Jncc
Parses the testing file, checking that all declarations are coherent with those already loaded from the training Arff file; if the classes are unknown, it reads only the instances, without looking for the classes.
parseIndicatorFile() - Method in class jncc20.Jncc.ResultsReporter
 
parseNbcNccPrediction(StringTokenizer) - Method in class jncc20.Jncc.ResultsReporter
Reads and evaluates a single Ncc prediction retrieved from the prediction file, and updates the indexes referring to NBC accuracy when NCC precise/imprecise
parseNbcPrediction(String) - Method in class jncc20.Jncc.ResultsReporter
Reads and assesses a single Nbc prediction retrieved from the prediction file; its accuracy or not on the supplied instance is tracked by the member variable nbcAccCurrentInst
parseNonMar() - Method in class jncc20.Jncc
Reads the file NonMar.txt, containing the list of nonMar variables; if no file is found, all variables are assumed to be MAR.
partitionPoints - Variable in class jncc20.NaiveCredalClassifier2
Partition Points, used when classyfing instances with missing units in the NonMar part.
pcClass - Variable in class jncc20.NaiveClassifier
prior counts for classes
pcCond - Variable in class jncc20.NaiveClassifier
prior counts for conditional frequencies
pcUncond - Variable in class jncc20.NaiveClassifier
prior counts for unconditional frequencies
possibleCutPoints - Variable in class jncc20.MdlDiscretizer
Numerical values of the feature, which constitues possible discretization intervals (i.e, possible cutPoints)
possibleCutPointsIdxInPairVector - Variable in class jncc20.MdlDiscretizer
Indexes of the possible cutPoints, with reference to PairVector
predictions - Variable in class jncc20.NaiveBayes
Index of the class predicted for each instance
predictions - Variable in class jncc20.NaiveCredalClassifier2
Stores NCC predictions; as every prediction can be imprecise and hence contain several value, it is implemented as a matrix.
predictionsFile - Variable in class jncc20.Jncc
Absolute path of the temporary predictions file
prepareDataSetFromRawData(ArrayList<double[]>, ArrayList<int[]>) - Method in class jncc20.Jncc
Take a raw set of data (undiscretized features) and put them into a dataset to be accessed by classifiers; categorical variables are copied unchanged, while numerical variables are converted to categorical according to DiscretizationIntervals; numerical variables discretized into a unique bin (and hence listed in NonUsedFeatures) are discarded.
prepareTrainTestSet(int) - Method in class jncc20.Jncc
Prepares training and testing sets for cross-validation, discretizing also numerical variables.
prepareTrainTestSet() - Method in class jncc20.Jncc
Prepares training and testing sets for validation via testing set, discretizing also numerical variables.
printArgError() - Static method in class jncc20.Jncc
 
printElapsedTime() - Method in class jncc20.Jncc
 
printHelp() - Static method in class jncc20.Jncc
Writes an help message to the user, specifying the syntax to be used with JNCC2.
probabilities - Variable in class jncc20.NaiveClassifier
Probabilities estimated for each class, for each instance
probabilitiesFile - Variable in class jncc20.Jncc
File that reports the estimated probabilities by precise classifiers and whether the imprecise classifier is precise or not; used to compute the curve of precision vs.

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