SYSTEMS AND METHODS FOR USING HASH TABLES FOR GENERATING TEXTUAL PREDICTION EXPLANATIONS

Systems and methods for using hash tables generating textual prediction explanations. In some aspects, the system receives a first plurality of user profiles and a corresponding plurality of resource availability values. Each user profile includes values for a first set of features. The system processes a first machine learning model to extract an explainability vector. The first machine learning model receives as input the first set of features and outputs a resource availability value. The system, using the explainability vector, selects a subset of features having corresponding values in the explainability vector above a threshold. The system generates a set of categories based on the subset of features and a hash table including the set of categories. The hash table is indexable using a hash value generated based on values for the subset of features. The system transmits to a user system corresponding a user profile a textual prediction explanation.