smile.classification

Class QDA.Trainer

java.lang.Object

smile.classification.ClassifierTrainer<double[]>

smile.classification.QDA.Trainer

Enclosing class:

QDA

public static class QDA.Trainer
extends ClassifierTrainer<double[]>

Trainer for quadratic discriminant analysis.

Constructor Summary

Constructors

Constructor and Description
QDA.Trainer() Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	setPriori(double[] priori) Sets a priori probabilities of each class.
void	setTolerance(double tol) Sets covariance matrix singularity tolerance.
QDA	train(double[][] x, int[] y) Learns a classifier with given training data.

Methods inherited from class smile.classification.ClassifierTrainer

setAttributes

Methods inherited from class java.lang.Object

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

Constructor Detail

QDA.Trainer

public QDA.Trainer()

Constructor. The default tolerance to covariance matrix singularity is 1E-4.

Method Detail

setPriori

public void setPriori(double[] priori)

Sets a priori probabilities of each class.

Parameters:

priori - a priori probabilities of each class.

setTolerance

public void setTolerance(double tol)

Sets covariance matrix singularity tolerance.

Parameters:

tol - a tolerance to decide if a covariance matrix is singular. The trainer will reject variables whose variance is less than tol².

train

public QDA train(double[][] x,
        int[] y)

Description copied from class: ClassifierTrainer

Learns a classifier with given training data.

Specified by:

train in class ClassifierTrainer<double[]>

Parameters:

x - the training instances.

y - the training labels.

Returns:

a trained classifier.