sktime.classification: Time series classification

The sktime.classification module contains algorithms and composition tools for time series classification.

Composition

ColumnEnsembleClassifier(estimators[, …])

Applies estimators to columns of an array or pandas DataFrame.

Dictionary-based

IndividualBOSS([window_size, word_length, …])

Single Bag of SFA Symbols (BOSS) classifier

BOSSEnsemble([threshold, max_ensemble_size, …])

Bag of SFA Symbols (BOSS)

ContractableBOSS([n_parameter_samples, …])

Contractable Bag of SFA Symbols (cBOSS) implementation of BOSS from [1] with refinements described in [2]

WEASEL([anova, bigrams, binning_strategy, …])

Word ExtrAction for time SEries cLassification (WEASEL) from [1].

MUSE([anova, bigrams, window_inc, …])

WEASEL+MUSE (MUltivariate Symbolic Extension) MUSE: implementation of multivariate version of WEASEL, referred to as just MUSE from [1]

IndividualTDE([window_size, word_length, …])

Single TDE classifier, based off the Bag of SFA Symbols (BOSS) model

TemporalDictionaryEnsemble([…])

Temporal Dictionary Ensemble (TDE) as described in [1].

Distance-based

KNeighborsTimeSeriesClassifier([…])

An adapted version of the scikit-learn KNeighborsClassifier to work with time series data.

ElasticEnsemble([distance_measures, …])

The Elastic Ensemble (EE) as described in Jason Lines and Anthony Bagnall, “Time Series Classification with Ensembles of Elastic Distance Measures”, Data Mining and Knowledge Discovery, 29(3), 2015.

ProximityForest([random_state, …])

Proximity Forest class to model a decision tree forest which uses distance measures to partition data, see [1].

ProximityTree([random_state, get_exemplars, …])

Proximity Tree class to model a decision tree which uses distance measures to partition data.

ProximityStump([random_state, …])

Proximity Stump class to model a decision stump which uses a distance measure to partition data.

Hybrid

HIVECOTEV1([stc_params, tsf_params, …])

Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) V1 as described in [1].

Interval-based

RandomIntervalSpectralForest([n_estimators, …])

Random Interval Spectral Forest (RISE) from [1]

SupervisedTimeSeriesForest([n_estimators, …])

Supervised Time Series Forest (STSF) classifier as described in [1].

Shapelet-based

ShapeletTransformClassifier([…])

Shapelet Transform Classifier

MrSEQLClassifier([seql_mode, symrep, …])

Time Series Classification with multiple symbolic representations and SEQL (Mr-SEQL)

ROCKETClassifier([num_kernels, ensemble, …])

Classifier wrapped for the ROCKET transformer using RidgeClassifierCV as the base classifier.