Systems and methods for improving prediction process using automated rule learning framework

A system for improving a model, the system comprising:

• a memory;
• and
• one or more processors coupled with the memory, wherein the one or more processors, when executed, perform operations comprising:
• receiving labelled data from one or more data sources;
• generating a plurality of segments from the labelled data using one or more tokenizers, wherein each of the segments is associated with one or more classes of a plurality of classes, and wherein the plurality of segments comprises a sub-plurality of unique segments;
• calculating an entropy value for each of the sub-plurality of unique segments;
• for each class in the plurality of classes, generating one or more rules based on each of the segments associated with the class and the entropy value of each such segment;
• and
• combining the generated one or more rules with a model to improve prediction performance of the model.

A non-transitory computer readable medium containing computer-readable instructions stored therein for causing a computer processor to perform operations comprising:

• receiving labelled data from one or more data sources;
• generating a plurality of segments from the labelled data using one or more tokenizers, wherein each of the segments is associated with one or more classes of a plurality of classes, and wherein the plurality of segments comprises a sub-plurality of unique segments;
• calculating an entropy value for each of the sub-plurality of unique segments;
• for each class in the plurality of classes, generating one or more rules based on each of the segments associated with the class and the entropy value of each such segment;
• and
• combining the generated one or more rules with a model to improve prediction performance of the model.