ai.libs.jaicore.ml.tsc.classifier.ensemble

Class EnsembleProvider

java.lang.Object

ai.libs.jaicore.ml.tsc.classifier.ensemble.EnsembleProvider

public class EnsembleProvider
extends java.lang.Object

Class statically providing preconfigured ensembles as commonly used in TSC implementations.

Method Summary

Modifier and Type	Method and Description
static weka.classifiers.Classifier	provideCAWPEEnsembleModel(int seed, int numFolds) Initializes the CAWPE ensemble model consisting of five classifiers (SMO, KNN, J48, Logistic and MLP) using a majority voting strategy.
static weka.classifiers.Classifier	provideHIVECOTEEnsembleModel(int seed, int numFolds) Initializes the HIVE COTE ensemble consisting of 7 classifiers using a majority voting strategy as described in J.

Methods inherited from class java.lang.Object

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

Method Detail

provideCAWPEEnsembleModel

public static weka.classifiers.Classifier provideCAWPEEnsembleModel(int seed,
                                                                    int numFolds)
                                                             throws java.lang.Exception

Initializes the CAWPE ensemble model consisting of five classifiers (SMO, KNN, J48, Logistic and MLP) using a majority voting strategy. The ensemble uses Weka classifiers. It refers to "Heterogeneous ensemble of standard classification algorithms" (HESCA) as described in Lines, Jason & Taylor, Sarah & Bagnall, Anthony. (2018). Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles. ACM Transactions on Knowledge Discovery from Data. 12. 1-35. 10.1145/3182382.

Parameters:

seed - Seed used within the classifiers and the majority confidence voting scheme

numFolds - Number of folds used within the determination of the classifier weights for the MajorityConfidenceVote

Returns:

Returns an initialized (but untrained) ensemble model.

Throws:

java.lang.Exception - Thrown when the initialization has failed

provideHIVECOTEEnsembleModel

public static weka.classifiers.Classifier provideHIVECOTEEnsembleModel(int seed,
                                                                       int numFolds)

Initializes the HIVE COTE ensemble consisting of 7 classifiers using a majority voting strategy as described in J. Lines, S. Taylor and A. Bagnall, "HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles for Time Series Classification," 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, 2016, pp. 1041-1046. doi: 10.1109/ICDM.2016.0133.

Parameters:

seed - Seed used within the classifiers and the majority confidence voting scheme

numFolds - Number of folds used within the determination of the classifier weights for the MajorityConfidenceVote

Returns:

Returns the initialized (but untrained) HIVE COTE ensemble model.