Evaluating impact of data feature deletion on associated policies

A system, comprising:

• a memory;
• and
• a processor communicatively coupled to the memory, wherein the processor is configured to perform a method comprising:
• obtaining, by the processor, models pretrained on a set of features;
• mapping, by the processor, a set of policies to the models;
• receiving, at the processor, a request to remove at least one feature from the features;
• in response to the receiving, identifying, by the processor using an association rule mining (ARM) model, a policy from the set of policies that is affected by the at least one feature;
• generating, by the processor using a performance evaluation model, performance scores for the models with and without the at least one feature;
• calculating, by the processor, a reward function for the at least one feature based on the identifying and the performance scores;
• determining, by the processor, that the reward function is greater than a threshold value;
• and
• generating, by the processor and in response to the determining, a recommendation for a user.

A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause a device to perform a method, the method comprising:

• obtaining, by the processor, models pretrained on a set of features;
• mapping, by the processor, a set of policies to the models;
• receiving, at the processor, a request to remove at least one feature from the features;
• in response to the receiving, identifying, by the processor using an association rule mining (ARM) model, a policy from the set of policies that is affected by the at least one feature;
• generating, by the processor using a performance evaluation model, performance scores for the models with and without the at least one feature;
• calculating, by the processor, a reward function for the at least one feature based on the identifying and the performance scores;
• determining, by the processor, that the reward function is greater than a threshold value;
• and
• generating, by the processor and in response to the determining, a recommendation for a user.