Jan-30-2020, 07:02 PM
Hello,
I am relatively new to Python and Machine Learning.
I have a basic dataset for insurance fraud and a script that generates the model and runs the predictions.
I am able to output the accuracy percentages, but I would like to also output the feature dependencies: For example, what role did each attribute play in the prediction? The policy_number would be 0.0% where as the claim_amount would likely be 56.2%, does this make sense?
Is there a scikit function for this? Also, is "feature dependency" even the correct term?
Thank you for your help!
-Matt
I am relatively new to Python and Machine Learning.
I have a basic dataset for insurance fraud and a script that generates the model and runs the predictions.
I am able to output the accuracy percentages, but I would like to also output the feature dependencies: For example, what role did each attribute play in the prediction? The policy_number would be 0.0% where as the claim_amount would likely be 56.2%, does this make sense?
Is there a scikit function for this? Also, is "feature dependency" even the correct term?
Thank you for your help!
-Matt