Package ai.libs.jaicore.ml.tsc.classifier.shapelets

Class LearnShapeletsClassifier

java.lang.Object

ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier<java.lang.Integer>

ai.libs.jaicore.ml.tsc.classifier.shapelets.LearnShapeletsClassifier

public class LearnShapeletsClassifier
extends ASimplifiedTSClassifier<java.lang.Integer>

LearnShapeletsClassifier published in "J. Grabocka, N. Schilling, M. Wistuba, L. Schmidt-Thieme: Learning Time-Series Shapelets" (https://www.ismll.uni-hildesheim.de/pub/pdfs/grabocka2014e-kdd.pdf). This classifier only supports univariate time series prediction.

Field Summary

Fields inherited from class ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier

classMapper, trained

Constructor Summary

Constructors

Constructor	Description
LearnShapeletsClassifier(int K, double learningRate, double regularization, int scaleR, double minShapeLengthPercentage, int maxIter, double gamma, int seed)	Constructor of the LearnShapeletsClassifier.
LearnShapeletsClassifier(int K, double learningRate, double regularization, int scaleR, double minShapeLengthPercentage, int maxIter, int seed)	Constructor of the LearnShapeletsClassifier.

Method Summary

Modifier and Type	Method	Description
LearnShapeletsLearningAlgorithm	getLearningAlgorithm(TimeSeriesDataset dataset)
double[][][]	getS()
double[][][]	getW()
double[]	getW0()
java.lang.Integer	predict(double[] univInstance)	Performs a prediction based on the given univariate double[] instance representation and returns the result.
java.util.List<java.lang.Integer>	predict(TimeSeriesDataset dataset)	Performs predictions based on the given instances in the given dataset.
java.lang.Integer	predict(java.util.List<double[]> multivInstance)	Performs a prediction based on the given multivariate list of double[] instance representation and returns the result.
void	setC(int c)	Setter for c
void	setEstimateK(boolean estimateK)	Enables / disabled the parameter estimation of K within the training algorithm.
void	setMinShapeLength(int minShapeLength)	Setter for LearnShapeletsClassifier#minShapeLength
void	setS(double[][][] s)	Setter for s
void	setW(double[][][] w)	Setter for w
void	setW0(double[] w0)	Setter for w0

Methods inherited from class ai.libs.jaicore.ml.tsc.classifier.ASimplifiedTSClassifier

checkWhetherPredictionIsPossible, getClassMapper, isTrained, setClassMapper, train

Methods inherited from class java.lang.Object

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

Constructor Detail

LearnShapeletsClassifier

public LearnShapeletsClassifier(int K,
                                double learningRate,
                                double regularization,
                                int scaleR,
                                double minShapeLengthPercentage,
                                int maxIter,
                                int seed)

Constructor of the LearnShapeletsClassifier.

Parameters:

K - See LearnShapeletsLearningAlgorithm#K

learningRate - See LearnShapeletsLearningAlgorithm#learningRate

regularization - See LearnShapeletsLearningAlgorithm#regularization

scaleR - See LearnShapeletsLearningAlgorithm#scaleR

minShapeLengthPercentage - See LearnShapeletsLearningAlgorithm#minShapeLengthPercentage

maxIter - See LearnShapeletsLearningAlgorithm#maxIter

seed - See LearnShapeletsLearningAlgorithm#seed

seed - See LearnShapeletsLearningAlgorithm.timeout

LearnShapeletsClassifier

public LearnShapeletsClassifier(int K,
                                double learningRate,
                                double regularization,
                                int scaleR,
                                double minShapeLengthPercentage,
                                int maxIter,
                                double gamma,
                                int seed)

Constructor of the LearnShapeletsClassifier.

Parameters:

K - See LearnShapeletsLearningAlgorithm#K

learningRate - See LearnShapeletsLearningAlgorithm#learningRate

regularization - See LearnShapeletsLearningAlgorithm#regularization

scaleR - See LearnShapeletsLearningAlgorithm#scaleR

minShapeLengthPercentage - See LearnShapeletsLearningAlgorithm#minShapeLengthPercentage

maxIter - See LearnShapeletsLearningAlgorithm#maxIter

seed - See LearnShapeletsLearningAlgorithm#seed

gamma - See LearnShapeletsLearningAlgorithm#gamma

Method Detail

setEstimateK

public void setEstimateK(boolean estimateK)

Enables / disabled the parameter estimation of K within the training algorithm.

Parameters:

estimateK - Value to be set

getS

public double[][][] getS()

Returns:

s.

setS

public void setS(double[][][] s)

Setter for s

Parameters:

s - New value to be set

getW

public double[][][] getW()

Returns:

w.

setW

public void setW(double[][][] w)

Setter for w

Parameters:

w - New value to be set

getW0

public double[] getW0()

Returns:

w0.

setW0

public void setW0(double[] w0)

Setter for w0

Parameters:

w0 - New value to be set

setC

public void setC(int c)

Setter for c

Parameters:

c - New value to be set

setMinShapeLength

public void setMinShapeLength(int minShapeLength)

Setter for LearnShapeletsClassifier#minShapeLength

Parameters:

minShapeLength - New value to be set

predict

public java.lang.Integer predict(double[] univInstance)
                          throws PredictionException

Performs a prediction based on the given univariate double[] instance representation and returns the result.

Specified by:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

univInstance - Univariate instance given by a double vector of time series values used for the prediction

Returns:

Returns the result of the prediction

Throws:

PredictionException - If something fails during the prediction process.

predict

public java.lang.Integer predict(java.util.List<double[]> multivInstance)
                          throws PredictionException

Performs a prediction based on the given multivariate list of double[] instance representation and returns the result.

Overrides:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

multivInstance - Multivariate instance given by a list of multiple double[] time series used for the prediction

Returns:

Returns the result of the prediction

Throws:

PredictionException - If something fails during the prediction process.

predict

public java.util.List<java.lang.Integer> predict(TimeSeriesDataset dataset)
                                          throws PredictionException

Performs predictions based on the given instances in the given dataset.

Specified by:

predict in class ASimplifiedTSClassifier<java.lang.Integer>

Parameters:

dataset - The TimeSeriesDataset for which predictions should be made.

Returns:

Returns the result of the predictions

Throws:

PredictionException - If something fails during the prediction process

getLearningAlgorithm

public LearnShapeletsLearningAlgorithm getLearningAlgorithm(TimeSeriesDataset dataset)

Specified by:

getLearningAlgorithm in class ASimplifiedTSClassifier<java.lang.Integer>