METHODS AND SYSTEMS FOR OPTIMIZED SELECTION OF DATA FEATURES FOR A NEURO-LINGUISTIC COGNITIVE ARTIFICAL INTELLIGENCE SYSTEM

摘要

Techniques are disclosed to optimize feature selection in generating betas for a feature dictionary of a neuro-linguistic Cognitive AI System. A machine learning engine receives a sample vector of input data to be analyzed by the neuro-linguistic Cognitive AI System. The neuro-linguistic Cognitive AI System is configured to generate multiple betas for each of a plurality of sensors. The machine learning engine identifies a sensor specified in the sample vector and selects optimization parameters for generating betas based on the identified sensor.