The problem is not only related with time series classification, but with any tabular data, where each target variable contains multiple
values per input feature var.
The question is:
could I use this package to explain anchor rules of a model trained with this format of data?
PD: This format would be quite similar to a B/W image classification dataset, where we have one image per sample and the labels are just numbers (NMIST example)
thanks for the excellent job.
I have created a dataset where each target variable has a 2D array. The dataset format is the one used by TSAI:
Considerations about our 3D input data or X vs a 2D target vars Y (my dataset are just numpy arrays)
here a diagram of the dataset format
The problem is not only related with time series classification, but with any tabular data, where each target variable contains multiple values per input feature var.
The question is:
could I use this package to explain anchor rules of a model trained with this format of data?
here a code example - 01_Intro_to_Time_Series_Classification.ipynb I am using to generate my own model
PD: This format would be quite similar to a B/W image classification dataset, where we have one image per sample and the labels are just numbers (NMIST example)