Uses of Class
LBJ2.classify.DiscreteFeature

Packages that use DiscreteFeature

LBJ2.classify	Contains classes representing classifiers and features, as well as utility classes related to classifiers and features that may come in handy.
LBJ2.learn	Learning algorithms, normalizers (used in inference; see Normalizer), testing metrics (used in cross validation; see TestingMetric), and other utility classes can be found in this package.

Uses of DiscreteFeature in LBJ2.classify

Subclasses of DiscreteFeature in LBJ2.classify

class

DiscreteArrayFeature A discrete array feature keeps track of its index in the classifier's returned array as well as the total number of features in that array.

Methods in LBJ2.classify with parameters of type DiscreteFeature

protected Feature	DiscreteFeature.conjunctWith(DiscreteFeature f, Classifier c) Create a feature representing the conjunction of this feature with the given argument feature.
protected Feature	DiscreteArrayFeature.conjunctWith(DiscreteFeature f, Classifier c) Create a feature representing the conjunction of this feature with the given argument feature.
protected Feature	RealFeature.conjunctWith(DiscreteFeature f, Classifier c) Create a feature representing the conjunction of this feature with the given argument feature.
protected Feature	RealArrayFeature.conjunctWith(DiscreteFeature f, Classifier c) Create a feature representing the conjunction of this feature with the given argument feature.
protected abstract Feature	Feature.conjunctWith(DiscreteFeature f, Classifier c) Create a feature representing the conjunction of this feature with the given argument feature.

Uses of DiscreteFeature in LBJ2.learn

Fields in LBJ2.learn declared as DiscreteFeature

protected DiscreteFeature

NaiveBayes.NaiveBayesVector.NaiveBayesIterator.currentFeature The feature corresponding to the current weight.