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Hi @kar10tik - there is the all_settings = ComprehensiveFCParameters()
reduced_setting = {key: value for key, value in all_settings.items() if key != "min"}
extract_features(..., kind_to_fc_parameters={"colA": all_settings, "colB": reuced_settings} |
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I'm using tsfresh to extract features comprehensively from a timeseries. I wish to exclude certain columns in my dataset from feature extraction (i.e., absolute energy, min, max, etc. shouldn't be computed based on a list of certain columns I can specify). Is there any way I can do this in tsfresh without having to remove the specific column(s) from the DataFrame to be input to
tsfresh.feature_extraction.extraction.extract_features()
or drop features starting with the specific column name(s) after the feature extraction is complete?Beta Was this translation helpful? Give feedback.
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