de.jungblut.classification

Interface Predictor

All Known Subinterfaces:

Classifier

All Known Implementing Classes:

AbstractClassifier, AbstractKNearestNeighbours, AbstractPredictor, DecisionTree, HMM, KNearestNeighbours, LogisticRegression, MaxEntMarkovModel, MultilayerPerceptron, MultinomialNaiveBayes, RandomForest, SparseKNearestNeighbours, UntrainableClassifier, Voter

public interface Predictor

Method Summary

Modifier and Type	Method and Description
default Classifier	asClassifier() Backward compatibility method to make online-ml project's predictors work with almost everything in this library.
int	extractPredictedClass(de.jungblut.math.DoubleVector predict) Given an already done prediction, choose the class.
int	extractPredictedClass(de.jungblut.math.DoubleVector predict, double threshold) Given an already done prediction, choose the class with a threshold.
de.jungblut.math.DoubleVector	predict(de.jungblut.math.DoubleVector features) Classifies the given features.
int	predictedClass(de.jungblut.math.DoubleVector features) Classifies the given features.
int	predictedClass(de.jungblut.math.DoubleVector features, double threshold) Classifies the given features.
de.jungblut.math.DoubleVector	predictProbability(de.jungblut.math.DoubleVector features) Classifies the given features.

Method Detail

predict

de.jungblut.math.DoubleVector predict(de.jungblut.math.DoubleVector features)

Classifies the given features.

Returns:

the vector that contains an indicator at the index of the class. Usually zero or 1, in some cases it is a probability or activation value.

predictProbability

de.jungblut.math.DoubleVector predictProbability(de.jungblut.math.DoubleVector features)

Classifies the given features.

Returns:

a vector that returns the probability of all outcomes. The output vector should sum to one.

predictedClass

int predictedClass(de.jungblut.math.DoubleVector features,
                   double threshold)

Classifies the given features.

Parameters:

threshold - the threshold for the prediction "probability". In the sigmoid and binary case, you want to set everything greater (>) 0.5 to 1d and everything below (<=) to 0d.

Returns:

the predicted class as an integer for the output of a classifier.

predictedClass

int predictedClass(de.jungblut.math.DoubleVector features)

Classifies the given features.

Returns:

the predicted class as an integer for the output of a classifier.

extractPredictedClass

int extractPredictedClass(de.jungblut.math.DoubleVector predict)

Given an already done prediction, choose the class.

Returns:

the class index as integer.

extractPredictedClass

int extractPredictedClass(de.jungblut.math.DoubleVector predict,
                          double threshold)

Given an already done prediction, choose the class with a threshold.

Returns:

the class index as integer.

asClassifier

default Classifier asClassifier()

Backward compatibility method to make online-ml project's predictors work with almost everything in this library.

Returns:

an untrainable classifer, wrapping the predictor inside.