sktime.transformations: Time series transformers¶
The sktime.transformations
module contains classes for data
transformations.
Panel transformers¶
Dictionary-based¶
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(PAA) Piecewise Aggregate Approximation Transformer, as described in Eamonn Keogh, Kaushik Chakrabarti, Michael Pazzani, and Sharad Mehrotra. |
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SFA (Symbolic Fourier Approximation) Transformer, as described in |
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SAX (Symbolic Aggregate approXimation) Transformer, as described in Jessica Lin, Eamonn Keogh, Li Wei and Stefano Lonardi, “Experiencing SAX: a novel symbolic representation of time series” Data Mining and Knowledge Discovery, 15(2):107-144 Overview: for each series: run a sliding window across the series for each window shorten the series with PAA (Piecewise Approximate Aggregation) discretise the shortened series into fixed bins form a word from these discrete values by default SAX produces a single word per series (window_size=0). SAX returns a pandas data frame where column 0 is the histogram (sparse pd.series) of each series. |
Summarize¶
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Transformer that finds segments of the same given value, plateau in the time series, and returns the starting indices and lengths. |
Transformer that segments time-series into random intervals and subsequently extracts series-to-primitives features from each interval. |
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Extract parameters of a fitted forecaster as features for a subsequent tabular learning task. |
tsfresh¶
Transformer for extracting and selecting features. |
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Transformer for extracting time series features |
Compose¶
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Applies transformations to columns of an array or pandas DataFrame. |
Transformer that concatenates multivariate time series/panel data into long univariate time series/panel data by simply concatenating times series in time. |
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Factory function for creating InstanceTransformer based on transform type |
Matrix profile¶
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Takes as input a time series dataset and returns the matrix profile and index profile for each time series of the dataset. |
PCA¶
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Transformer that applies Principle Components Analysis to a univariate time series. |
Reduce¶
A transformer that turns time series/panel data into tabular data. |
Rocket¶
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ROCKET |
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MINIROCKET |
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MINIROCKET (Multivariate) |
Segment¶
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Interval segmentation transformer. |
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Transformer that segments time-series into random intervals with random starting points and lengths. |
Shapelet¶
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Shapelet Transform. |
Contracted Shapelet Transform. @incollection{bostrom2017binary, title={Binary shapelet transform for multiclass time series classification}, author={Bostrom, Aaron and Bagnall, Anthony}, booktitle={Transactions on Large-Scale Data-and Knowledge-Centered Systems XXXII}, pages={24–46}, year={2017}, publisher={Springer} }. |
Series transformers¶
Detrend¶
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Remove a trend from a series. |
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A transformer that removes a seasonal and trend components from time series |
A transformer that removes a seasonal and trend components from time series, conditional on seasonality test. |
Adapt¶
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Adaptor for scikit-learn-like tabular transformations to series setting. |
Box-cox¶
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Auto-correlation¶
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Auto-correlation transformer. |
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Partial auto-correlation transformer. |
Cosine¶
Matrix Profile¶
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HampelFilter¶
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HampelFilter to detect outliers based on a sliding window. |