- Transformers (simple)
- Transformers (paired)
- Time series classifiers
- Time series regressors
- Forecasters
Simple (or first-degree) transformations:
Name | Class | Maintainer | References |
---|---|---|---|
e.g. Fitted parameter feature extraction |
Name | Class | Maintainer | References |
---|---|---|---|
e.g. Fourier transform |
Name | Class | Maintainer | References |
---|---|---|---|
Interval segmenter (fixed) | transformers.compose.IntervalSegmenter | @mloning | |
Interval segmenter (random) | transformers.compose.RandomIntervalSegmenter | @mloning | |
Piecewise Aggregate Approximation | transformers.panel.dictionary_based._paa.PAA | @MatthewMiddlehurst | Keogh et al (2001) - Dimensionality reduction for fast similarity search in large time series databases |
Symbolic Aggregate Approximation | transformers.panel.dictionary_based._sax.SAX | @MatthewMiddlehurst | Lin et al (2007) - Experiencing SAX: a novel symbolic representation of time series |
Symbolic Fourier Approximation | transformers.panel.dictionary_based._sfa.SFA | @MatthewMiddlehurst | Schäfer (2012) - SFA: a symbolic fourier approximation and index for similarity |
Name | Class | Maintainer | References |
---|---|---|---|
Tabularise (UK) | transformers.compose.Tabulariser | @mloning | |
Tabularize (US) | transformers.compose.Tabularizer | @mloning | |
Auto-correlation function | transformers.spectral_based.AutoCorrelationFourierTransformer | @jsellier | |
Cosine Transform | transformers.spectral_based.CosineTransformer | @jsellier | |
Discrete Fourier Transform | transformers.spectral_based.DiscreteFourierTransformer | @jsellier | |
Power Spectrum | transformers.spectral_based.PowerSpectrumTransformer | @jsellier | |
tsfresh Feature Extractor | transformers.summarise._tsfresh.TSFreshFeatureExtractor | @mloning @Ayushmaanseth | |
tsfresh Relevant Feature Extractor | transformers.summarise._tsfresh.TSFreshRelevantFeatureExtractor | @mloning @Ayushmaanseth | |
Derivative Series | transformers.summarise.DeriativeSlopeTransformer | @mloning | |
Plateau Finder | transformers.summarise.PlateauFinder | @mloning | |
Random Interval Feature Extractor | transformers.summarise.RandomIntervalFeatureExtractor | @mloning | |
Matrix profile | transformers.matrix_profile | Claudia Rincon Sanchez | (custom implementation) |
Principal component scores after tabularization | transformers.PCATransformer | @prockenschaub | Hotelling (1933) - Analysis of a complex of statistical variables into principal components |
Shapelet transform | transformers.ShapeletTransform | @jasonlines | Hills et al (2014) - Classification of time series by shapelet transformation |
Shapelet transform (contracted) | transformers.ContractedShapeletTransform | @jasonlines | Hills et al (2014) - Classification of time series by shapelet transformation |
Shapelet transform (random sampled) | transformers.RandomEnumerationShapeletTransform | @jasonlines | Hills et al (2014) - Classification of time series by shapelet transformation |
ROCKET | transformers.rocket.Rocket | @angus924 | Dempser et al (2019) ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels |
Canonical Time-series Characteristics | contrib.transformers.catch22_features.Catch22 | @MatthewMiddlehurst | Lubba et al (2019) - catch22: CAnonical Time-series CHaracteristics |
Name | Class | Maintainer | References |
---|---|---|---|
Concatenate variables | transformers.compose.ColumnConcatenator | @mloning |
| Name | Class | Maintainer | References | | ------| ------ | ------- | ------ | ------- | | n-ts-to-X | Concatenate column-wise | transformers.compose.ColumnTransformer | @mloning | | | n-ts-to-X | Feature union | pipeline.FeatureUnion | @mloning | |
From/output | To/input | Name | Class | Maintainer | References |
---|---|---|---|---|---|
n-ts-to-df | 1-ts-to-df | Apply row-wise | transformers.compose.RowwiseTransformer | @mloning |
Paired (or second-degree) transformations:
Note: the interface for 2nd degree transformers is currently under re-factoring, and currently not consistent or homogenous.
Name | Class | Maintainer | References |
---|---|---|---|
BOSS Distance | classification.dictionary_based._boss.boss_distance | @MatthewMiddlehurst | Schäfer (2014) - The BOSS is concerned with time series classification in the presence of noise |
Histogram Intersection | classification.dictionary_based._tde.histogram_intersection | @MatthewMiddlehurst |
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
BOSS Ensemble | classification.dictionary_based._boss.BOSSEnsemble | @MatthewMiddlehurst | Schäfer (2014) - The BOSS is concerned with time series classification in the presence of noise |
BOSS Atom | classification.dictionary_based._boss.IndividualBOSS | @MatthewMiddlehurst | |
cBOSS | classification.dictionary_based._cboss.ContractableBOSS | @MatthewMiddlehurst | Middlehurst et al (2019) - Scalable dictionary classifiers for time series classification |
Temporal Dictionary Ensemble (TDE) | classification.dictionary_based._tde.TemporalDictionaryEnsemble | @MatthewMiddlehurst | Middlehurst et al (2020) - The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification |
TDE Atom | classification.dictionary_based._tde.IndividualTDE | @MatthewMiddlehurst | |
Elastic Ensemble | classification.distance_based._elastic_ensemble.ElasticEnsemble | @jasonlines | Lines, Bagnall (2015) - Time Series Classification with Ensembles of Elastic Distance Measures |
Proximity Forest | classification.distance_based._proximity_forest.ProximityForest | @goastler | Lucas et al (2019) - Proximity Forest: an effective and scalable distance-based classifier for time series |
Proximity Stump | classification.distance_based._proximity_forest.ProximityStump | @goastler | Lucas et al (2019) - Proximity Forest: an effective and scalable distance-based classifier for time series |
Random Interval Spectral Forest (RISE) | classification.frequency_based._rise.RandomIntervalSpectralForest | @TonyBagnall | Lines et al (2018) - Time Series Classification with HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles |
Shapelet Transform Classifier | classification.shapelet_based._stc.ShapeletTransformClassifier | @TonyBagnall | Hills et al (2014) - Classification of time series by shapelet transformation |
Time Series Forest | classification.interval_based._tsf.TimeSeriesForestClassifier | @TonyBagnall | Deng et al (2013) - A Time Series Forest for Classification and Feature Extraction |
Time Series k-NN | classification.distance_based._time_series_neighbors.KNeighborsTimeSeriesClassifier | @jasonlines | |
Mr-SEQL | classification.shapelet_based.mrseql.mrseql.MrSEQLClassifier | @lnthach | Interpretable Time Series Classification Using Linear Models and Multi-resolution Multi-domain Symbolic Representations |
ShapeDTW | classification.distance_based._shape_dtw.ShapeDTW | @Multivin12 | shapeDTW: Shape Dynamic Time Warping |
WEASEL | classification.dictionary_based._weasel.WEASEL | @patrickZIB | Fast and Accurate Time Series Classification with WEASEL |
catch22 Forest Classifier | contrib.hybrid._catch22_forest_classifier.Catch22ForestClassifier | @MatthewMiddlehurst | Lubba et al (2019) - catch22: CAnonical Time-series CHaracteristics |
Canonical Interval Forest (CIF) | contrib.interval_based.cif._CanonicalIntervalForest | @MatthewMiddlehurst | Middlehurst et al (2020) - The Canonical Interval Forest (CIF) Classifier for Time Series Classification |
name | sktime class | maintainer | literature |
---|---|---|---|
WEASEL+MUSE | classifiers.dictionary_based.weasel.MUSE | @patrickZIB | Multivariate time series classification with WEASEL+ MUSE |
(only abstract ensembles in this list - hard-coded ensembles go in one of the lists for atoms)
Of | Name | Class | Maintainer | References |
---|---|---|---|---|
univariate TSC | boosting TSC | classifiers.compose.ensemble.TimeSeriesForestClassifier | @mloning |
Components | Name | Class | Maintainer | References |
---|---|---|---|---|
Transformers, classifiers, regressors | pipeline | sktime.pipeline.Pipeline |
From/output | To/input | Name | Class | Maintainer | References |
---|---|---|---|---|---|
multivariate TSC | univariate TSC | column ensembler | classifiers.compose.column_ensembler.ColumnEnsembleClassifier | @abostrom |
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
Naive forecaster | NaiveForecaster | @mloning | |
Holt-Winters exponential smoothing forecaster | ExpSmoothingForecaster | @mloning, @big-o | |
Theta forecaster | ThetaForecaster | @big-o | Unmasking the Theta method |
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
Name | Class | Maintainer | References |
---|---|---|---|
Online Hedge Ensemble Forecasting | sktime.forecasting.online_ensemble.OnlineEnsembleForecaster | @magittan | A Parameter-free Hedging Algorithm |
name | sktime class | maintainer | literature |
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Name | Class | Maintainer | References |
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