Data analysis and rule generation for providing a recommendation

Abstract

Provided are techniques for data analysis and rule generation for providing a recommendation. A recommendation structure is built from features of data, where the recommendation structure comprises a plurality of rules, and where each rule of the plurality of rules is associated with a recommendation. The recommendation structure is sent to a model. A feature set comprising a feature and one or more related features is created from the features. In response to determining that a feature worthiness score of the feature set exceeds a threshold, the feature set is input to the model. A rule of the plurality of rules is received from the model, where the rule includes the feature, the one or more related features, and the associated recommendation. In response to receiving a set of values for the feature and the one or more related features, the rule is applied to the set of values to provide the recommendation.