sktime.classification: Time series classification¶
The sktime.classification
module contains algorithms and composition tools for time series classification.
Composition¶
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Applies estimators to columns of an array or pandas DataFrame. |
Dictionary-based¶
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Single Bag of SFA Symbols (BOSS) classifier |
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Bag of SFA Symbols (BOSS) |
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Contractable Bag of SFA Symbols (cBOSS) implementation of BOSS from [1] with refinements described in [2] |
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Word ExtrAction for time SEries cLassification (WEASEL) from [1]. |
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WEASEL+MUSE (MUltivariate Symbolic Extension) MUSE: implementation of multivariate version of WEASEL, referred to as just MUSE from [1] |
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Single TDE classifier, based off the Bag of SFA Symbols (BOSS) model |
Temporal Dictionary Ensemble (TDE) as described in [1]. |
Distance-based¶
An adapted version of the scikit-learn KNeighborsClassifier to work with time series data. |
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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. |
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Proximity Forest class to model a decision tree forest which uses distance measures to partition data, see [1]. |
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Proximity Tree class to model a decision tree which uses distance measures to partition data. |
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Proximity Stump class to model a decision stump which uses a distance measure to partition data. |
Hybrid¶
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Hierarchical Vote Collective of Transformation-based Ensembles (HIVE-COTE) V1 as described in [1]. |
Interval-based¶
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Random Interval Spectral Forest (RISE) from [1] |
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Supervised Time Series Forest (STSF) classifier as described in [1]. |
Shapelet-based¶
Shapelet Transform Classifier |
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Time Series Classification with multiple symbolic representations and SEQL (Mr-SEQL) |
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Classifier wrapped for the ROCKET transformer using RidgeClassifierCV as the base classifier. |