Data mining, Insurance and Knowledge Discovery

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

plot.barh(figsize=(10,12)); We see that the top 5 features with most significant influence on the prediction are: checking_account_A14: absence of a checking account status_A93: personal status and sex – single male property_A123: owns property different to real estate, savings agreement, or life insurance (e.g. nn_importances.tail(25).plot.barh(figsize=(10,12));

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Explaining black-box models using attribute importance, PDPs, and LIME

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