smile.classification

Interface Classifier<T>

Type Parameters:

T - the type of input object

All Superinterfaces:

java.io.Serializable, java.util.function.ToDoubleFunction<T>, java.util.function.ToIntFunction<T>

All Known Subinterfaces:

OnlineClassifier<T>, SoftClassifier<T>

All Known Implementing Classes:

AdaBoost, DecisionTree, DiscreteNaiveBayes, FLD, GradientTreeBoost, KNN, LDA, LogisticRegression, LogisticRegression.Binomial, LogisticRegression.Multinomial, Maxent, Maxent.Binomial, Maxent.Multinomial, MLP, NaiveBayes, OneVersusOne, OneVersusRest, QDA, RandomForest, RBFNetwork, RDA, SparseLogisticRegression, SparseLogisticRegression.Binomial, SparseLogisticRegression.Multinomial, SVM

public interface Classifier<T>
extends java.util.function.ToIntFunction<T>, java.util.function.ToDoubleFunction<T>, java.io.Serializable

A classifier assigns an input object into one of a given number of categories. The input object is formally termed an instance, and the categories are termed classes. The instance is usually described by a vector of features, which together constitute a description of all known characteristics of the instance.

Classification normally refers to a supervised procedure, i.e. a procedure that produces an inferred function to predict the output value of new instances based on a training set of pairs consisting of an input object and a desired output value. The inferred function is called a classifier if the output is discrete or a regression function if the output is continuous.

Method Summary

Modifier and Type	Method and Description
default double	applyAsDouble(T x)
default int	applyAsInt(T x)
default double	f(T x) Returns the real-valued decision function value.
int	predict(T x) Predicts the class label of an instance.
default int[]	predict(T[] x) Predicts the class labels of an array of instances.

Method Detail

predict

int predict(T x)

Predicts the class label of an instance.

Parameters:

x - the instance to be classified.

Returns:

the predicted class label.

f

default double f(T x)

Returns the real-valued decision function value.

Parameters:

x - the instance to be classified.

Returns:

the prediction score.

predict

default int[] predict(T[] x)

Predicts the class labels of an array of instances.

Parameters:

x - the instances to be classified.

Returns:

the predicted class labels.

applyAsInt

default int applyAsInt(T x)

Specified by:

applyAsInt in interface java.util.function.ToIntFunction<T>

applyAsDouble

default double applyAsDouble(T x)

Specified by:

applyAsDouble in interface java.util.function.ToDoubleFunction<T>