Package de.jungblut.classification
Interface Predictor
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- 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
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default ClassifierasClassifier()Backward compatibility method to make online-ml project's predictors work with almost everything in this library.intextractPredictedClass(de.jungblut.math.DoubleVector predict)Given an already done prediction, choose the class.intextractPredictedClass(de.jungblut.math.DoubleVector predict, double threshold)Given an already done prediction, choose the class with a threshold.de.jungblut.math.DoubleVectorpredict(de.jungblut.math.DoubleVector features)Classifies the given features.intpredictedClass(de.jungblut.math.DoubleVector features)Classifies the given features.intpredictedClass(de.jungblut.math.DoubleVector features, double threshold)Classifies the given features.de.jungblut.math.DoubleVectorpredictProbability(de.jungblut.math.DoubleVector features)Classifies the given features.
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Method Detail
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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.
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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.
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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.
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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.
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extractPredictedClass
int extractPredictedClass(de.jungblut.math.DoubleVector predict)
Given an already done prediction, choose the class.- Returns:
- the class index as integer.
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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.
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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.
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