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

A task complexity learning system, comprising:

• a machine learning model configured to predict the values of a continuous task variable y based upon an input variable x;
• a machine learning encoder configured to encode a continuous task variable y into and encoded task value;
• a loss function configured to calculate a loss based upon the predicted value of y output by the model and the encoded task value output by the encoder;
• and
• a distortion function configured to calculate the distortion based upon the input continuous task variable y and the encoded task value,
• wherein the model and the encoder are trained by minimizing an objective function based upon a hyperparameter λ, the loss function, and the distortion function for a set of input training data including x, y pairs.

A non-transitory machine-readable storage medium encoded with instructions for implementing a task complexity learning system, comprising:

• instructions for learning a model for predicting the value of a continuous task variable y based upon an input variable x;
• instructions for learning an encoder that encodes a continuous task variable y into an encoded task value;
• instructions for calculating a loss function based upon the predicted value of y output by the model and the encoded task value output by the encoder;
• and
• instructions for 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 a hyperparameter λ, the loss function, and the distortion function for a set of input training data including x, y pairs.