System to identify and explore relevant predictive analytics tasks of clinical value and calibrate predictive model outputs to a prescribed minimum level of predictive accuracy

Abstract

A method of implementing a task complexity learning system, including: learning a model for predicting the value of a continuous task variable y based upon an input variable x; learning an encoder that encodes a continuous task variable y into an encoded task value; calculating a loss function based upon the predicted value of y output by the model and the encoded task value output by the encoder; calculating a distortion function based upon the input continuous task variable y and the encoded task value, wherein learning the model and learning the encoder includes minimizing an objective function based upon the loss function and the distortion function for a set of input training data including x, y pairs.