#mlforecast
Title
s
Slackbot
07/13/2023, 4:04 PMThis message was deleted.
j
José Morales
07/14/2023, 5:55 PMHey. I think you need the features used to compute the predictions as well. You can use the before_predict_callback argument of the predict method to save them and use these to compute the shap values afterwards
m
Max (Nixtla)
07/16/2023, 5:57 PM@Rehan Javed, were you able to solve this?
j
José Morales
07/17/2023, 7:39 PMI can provide a full example in a few of hours, but my idea is something like:
Copy code
from functools import partial
def extract_features(df, save_list):
save_list.append(df)
return df
save_list = []
extract_features_callback = partial(extract_features, save_list=save_list)
# pass this callback to predict
features = pd.concat(save_list)You need to pass the one with the partial applied, the extract_features_callback
Yes, those are sorted by id and date. Glad it worked, I'll add a callaback to the library that does this so that you can use it in the future
🙌 1
2 Views