Interpret explainer module question

I ran a forecasting experiment in Azure ML and it chose SeasonalAverage algorithm as the best model. In the explanation, only the target column ‘WeeklySales’ had importance and none of the other input columns (CustomerType, CustomerClass) seem to have any importance. I wanted to force the model to use other input columns. I couldn’t find a way force it in my python script, so I opened a MS support case. They came back and mentioned there was no way to force the model to use the other input columns. I could instead use the interpret package explainer to understand as to why. I tried to use the TabularExplainer, MimicExplainer and PFIExplainer modules, but I get the error “For a forecasting model, predict is not supported. Please use forecast instead.”. I do use forecasting task in the automl_config. MS support suggested that I get in touch with the developers and they also suggested that the explainer modules might not have been designed for time series.

I would appreciate your suggestion.

Thank you Kannan

[kannanthiru1]

Hello IIya

In the attached script ‘SKU Forecasting 12’,

1. for Tabular Explainer I am getting the error in line 155
2. for Mimic Explainer, the line is 172
3. for PFI explainer, the line is 185

I would appreciate your help. Kannan SKU Forecasting 12.txt

[kannanthiru1]

Thank you Ilya for following up. I deeply appreciate it. Kannan