Mission accomplished

The mission was to understand why one of your client’s bars is Outstanding while another one is Disappointing. Your approach employed the interpretation of machine learning models to arrive at the following conclusions:

• According to SHAP on the tabular model, the Outstanding bar owes that rating to its berry taste and its cocoa percentage of 70%. On the other hand, the unfavorable rating for the Disappointing bar is due mostly to its earthy flavor and bean country of origin (Other). Review date plays a smaller role, but it seems that chocolate bars reviewed in that period (2013–15) were at an advantage.
• LIME confirms that cocoa_percent<=70 is a desirable property, and that, in addition to berry, creamy, cocoa, and rich are favorable tastes, while sweet, sour, and molasses are unfavorable.
• The commonality between both methods using the tabular model is that despite the many non-taste-related attributes, taste features are...