Add a new argument to the custom.timeseries_preprocessing.rolling_window_sequences primitive to be able to selectively drop some of the generated sequences.
This should be new produce argument called drop which indicates which values in the timeseries sequence are invalid and have to be dropped. This argument would be required=False, following this specification.
The input can be of several types:
numpy.ndarray (or array-like): 1d array-like object of boolean (or binary integer) values that indicate which values are invalid. This references both to X and y indexes.
None, str, int, float or bool: Any window that contains this value within X or y will be dropped.
Additionally, a second argument called drop_windows should be added to disable the dropping altogether. This should be set as a fixed hyperparameter with default value False to keep the current behavior by default.
Add a new argument to the
custom.timeseries_preprocessing.rolling_window_sequencesprimitive to be able to selectively drop some of the generated sequences.This should be new
produceargument calleddropwhich indicates which values in the timeseries sequence are invalid and have to be dropped. This argument would berequired=False, following this specification.The input can be of several types:
numpy.ndarray(or array-like): 1d array-like object of boolean (or binary integer) values that indicate which values are invalid. This references both to X and y indexes.None,str,int,floatorbool: Any window that contains this value withinXorywill be dropped.Additionally, a second argument called
drop_windowsshould be added to disable the dropping altogether. This should be set as a fixed hyperparameter with default valueFalseto keep the current behavior by default.