smile.classification

Interface Classifier<T>

Type Parameters:

T - the type of input object

All Known Subinterfaces:

OnlineClassifier<T>, SoftClassifier<T>

All Known Implementing Classes:

AdaBoost, DecisionTree, FLD, GradientTreeBoost, KNN, LDA, LogisticRegression, Maxent, NaiveBayes, NeuralNetwork, QDA, RandomForest, RBFNetwork, RDA, SVM

public interface Classifier<T>

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
int	predict(T x) Predicts the class label of an instance.

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