pyFTS.models.incremental package¶
Module contents¶
FTS methods with incremental/online learning
Submodules¶
pyFTS.models.incremental.TimeVariant module¶
Meta model that wraps another FTS method and continously retrain it using a data window with the most recent data
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class
pyFTS.models.incremental.TimeVariant.Retrainer(**kwargs)¶ Bases:
pyFTS.common.fts.FTSMeta model for incremental/online learning
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forecast(data, **kwargs)¶ Point forecast one step ahead
Parameters: - data – time series data with the minimal length equal to the max_lag of the model
- kwargs – model specific parameters
Returns: a list with the forecasted values
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train(data, **kwargs)¶ Method specific parameter fitting
Parameters: - data – training time series data
- kwargs – Method specific parameters
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pyFTS.models.incremental.IncrementalEnsemble module¶
Time Variant/Incremental Ensemble of FTS methods
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class
pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS(**kwargs)¶ Bases:
pyFTS.models.ensemble.ensemble.EnsembleFTSTime Variant/Incremental Ensemble of FTS methods
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forecast(data, **kwargs)¶ Point forecast one step ahead
Parameters: - data – time series data with the minimal length equal to the max_lag of the model
- kwargs – model specific parameters
Returns: a list with the forecasted values
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train(data, **kwargs)¶ Method specific parameter fitting
Parameters: - data – training time series data
- kwargs – Method specific parameters
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