public abstract class AbstractClassifier extends AbstractPredictor implements Classifier
| Constructor and Description |
|---|
AbstractClassifier() |
| Modifier and Type | Method and Description |
|---|---|
void |
train(de.jungblut.math.DoubleVector[] features,
de.jungblut.math.DoubleVector[] outcome)
Trains this classifier with the given features and the outcome.
|
void |
train(Iterable<de.jungblut.math.DoubleVector> features,
Iterable<de.jungblut.math.DoubleVector> outcome)
Trains this classifier with the given features and the outcome.
|
extractPredictedClass, extractPredictedClass, predictedClass, predictedClass, predictProbabilityclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitasClassifier, extractPredictedClass, extractPredictedClass, predict, predictedClass, predictedClass, predictProbabilitypublic void train(de.jungblut.math.DoubleVector[] features,
de.jungblut.math.DoubleVector[] outcome)
Classifiertrain in interface Classifieroutcome - the outcome must have classes labeled as doubles. E.G. in
the binary case you have a single element and decide between 0d
and 1d. In higher dimensional cases you have each of these single
elements mapped to a dimension.public void train(Iterable<de.jungblut.math.DoubleVector> features, Iterable<de.jungblut.math.DoubleVector> outcome)
Classifiertrain in interface Classifieroutcome - the outcome must have classes labeled as doubles. E.G. in
the binary case you have a single element and decide between 0d
and 1d. In higher dimensional cases you have each of these single
elements mapped to a dimension.Copyright © 2016. All rights reserved.