PREDICTIVE DATA ANALYSIS USING CUSTOM-PARAMETERIZED DIMENSIONALITY REDUCTION

摘要

There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing/executing predictive data analysis using custom-parameterized dimensionality reduction. In one example, a method includes identifying a group of predictive input features and one or more predictive markers; determining a per-marker feature for each predictive marker; determining one or more refined features for the group of predictive input features based at least in part on each per-marker feature for a predictive marker; performing the predictive inference based at least in part on the one or more refined features to generate one or more predictions; and performing one or more prediction-based actions based at least in pat on the one or more predictions.