ai.libs.jaicore.ml.tsc.shapelets.search

Class EarlyAbandonMinimumDistanceSearchStrategy

java.lang.Object

ai.libs.jaicore.ml.tsc.shapelets.search.AMinimumDistanceSearchStrategy

ai.libs.jaicore.ml.tsc.shapelets.search.EarlyAbandonMinimumDistanceSearchStrategy

public class EarlyAbandonMinimumDistanceSearchStrategy
extends AMinimumDistanceSearchStrategy

Class implementing a search strategy used for finding the minimum distance of a Shapelet object to a time series. The approach uses early abandoning as described in algorithm 2 in the paper 'Jason Lines, Luke M. Davis, Jon Hills, and Anthony Bagnall. 2012. A shapelet transform for time series classification. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '12). ACM, New York, NY, USA, 289-297.'.

Field Summary

Fields inherited from class ai.libs.jaicore.ml.tsc.shapelets.search.AMinimumDistanceSearchStrategy

useBiasCorrection

Constructor Summary

Constructors

Constructor and Description
EarlyAbandonMinimumDistanceSearchStrategy(boolean useBiasCorrection) Standard constructor.

Method Summary

Modifier and Type	Method and Description
double	findMinimumDistance(Shapelet shapelet, double[] timeSeries) Optimized function returning the minimum distance among all subsequences of the given timeSeries to the shapelet's data.

Methods inherited from class java.lang.Object

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

Constructor Detail

EarlyAbandonMinimumDistanceSearchStrategy

public EarlyAbandonMinimumDistanceSearchStrategy(boolean useBiasCorrection)

Standard constructor.

Parameters:

useBiasCorrection - See AMinimumDistanceSearchStrategy.useBiasCorrection

Method Detail

findMinimumDistance

public double findMinimumDistance(Shapelet shapelet,
                                  double[] timeSeries)

Optimized function returning the minimum distance among all subsequences of the given timeSeries to the shapelet's data. This function implements the algorithm 2 mentioned in the original paper. It performs the similarity search with online normalization and early abandon.

Specified by:

findMinimumDistance in class AMinimumDistanceSearchStrategy

Parameters:

shapelet - The shapelet to be compared to all subsequences

timeSeries - The time series which subsequences are compared to the shapelet's data

Returns:

Return the minimum distance among all subsequences