smile.classification

Class ClassifierTrainer<T>

java.lang.Object

smile.classification.ClassifierTrainer<T>

Type Parameters:

T - the type of input object.

Direct Known Subclasses:

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

public abstract class ClassifierTrainer<T>
extends java.lang.Object

Abstract classifier trainer.

Constructor Summary

Constructors

Constructor and Description
ClassifierTrainer() Constructor.
ClassifierTrainer(smile.data.Attribute[] attributes) Constructor.

Method Summary

Modifier and Type	Method and Description
void	setAttributes(smile.data.Attribute[] attributes) Sets feature attributes.
abstract Classifier<T>	train(T[] x, int[] y) Learns a classifier with given training data.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ClassifierTrainer

public ClassifierTrainer()

Constructor.

ClassifierTrainer

public ClassifierTrainer(smile.data.Attribute[] attributes)

Constructor.

Parameters:

attributes - the attributes of independent variable.

Method Detail

setAttributes

public void setAttributes(smile.data.Attribute[] attributes)

Sets feature attributes. This is optional since most classifiers can only work on real-valued attributes.

Parameters:

attributes - the feature attributes.

train

public abstract Classifier<T> train(T[] x,
                                    int[] y)

Learns a classifier with given training data.

Parameters:

x - the training instances.

y - the training labels.

Returns:

a trained classifier.