Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
'ablation' feature importance sometimes show wrong wrong accuracy_change sign and therefore wrong order.
'accuracy_change' needs sometimes to be multiplied by -1, but not always.
then sorted again by accuracy change, so its results are similar to 'permutation method' results
Thanks for the great work!
PD: Could you confirm that the most important features will be those with a lower value on its accuracy result? (since higher accuracy is better, so low accuracy when not using this feature means this feature was important).
Just one small error I found
https://github.com/timeseriesAI/tsai/blob/main/tsai/analysis.py#L132
'ablation' feature importance sometimes show wrong wrong accuracy_change sign and therefore wrong order. 'accuracy_change' needs sometimes to be multiplied by -1, but not always. then sorted again by accuracy change, so its results are similar to 'permutation method' results
Thanks for the great work!
PD: Could you confirm that the most important features will be those with a lower value on its accuracy result? (since higher accuracy is better, so low accuracy when not using this feature means this feature was important).