Package ai.libs.jaicore.basic.metric

This package contains implementations for time series distance measures.

Interface Summary

Interface	Description
IAbandonable	Interface for Distance measures that can make use of the Early Abandon technique.

Class Summary

Class	Description
AWeightedTrigometricDistance
ComplexityInvariantDistance	Implementation of the Complexity Invariant Distance (CID) measure as published in "A Complexity-Invariant Distance Measure for Time Series" by Gustavo E.A.P.A.
ConfusionMetrics	A util class for handling confusion matrix metrics that are solely based on counts of true positives (tp), false positives (fp), true negatives (tn), and false negatives (fn).
DerivateDistance	Implementation of the Derivate Distance (DD) measure as published in "Using derivatives in time series classification" by Tomasz Gorecki and Maciej Luczak (2013).
DerivateTransformDistance	Implementation of the Derivate Transform Distance (TD) measure as published in "Non-isometric transforms in time series classification using DTW" by Tomasz Gorecki and Maciej Luczak (2014).
DynamicTimeWarping	Implementation of the Dynamic Time Warping (DTW) measure as published in "Using Dynamic Time Warping to FindPatterns in Time Series" Donald J.
EuclideanDistance	Implementation of the Euclidean distance for time series.
ManhattanDistance	Implementation of the Manhattan distance for time series.
MoveSplitMerge	Implementation of the Move-Split-Merge (MSM) measure as published in "The Move-Split-Merge Metric for Time Series" by Alexandra Stefan, Vassilis Athitsos and Gautam Das (2013).
ScalarDistanceUtil	ScalarDistanceUtil
ShotgunDistance	Implementation of Shotgun Distance measure as published in "Towards Time Series Classfication without Human Preprocessing" by Patrick Schäfer (2014).
TimeWarpEditDistance	Time Warp Edit Distance as published in "Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching" by Pierre-Francois Marteau (2009).
TransformDistance	Implementation of the Transform Distance (TD) measure as published in "Non-isometric transforms in time series classification using DTW" by Tomasz Gorecki and Maciej Luczak (2014).
WeightedDynamicTimeWarping	Implementation of the Dynamic Time Warping (DTW) measure as published in "Weighted dynamic time warping for time series classification" by Young-Seon Jeong, Myong K.