Amazon.com, Inc.
Tuning of machine learning models using accuracy metrics selected to increase performance

Abstract:

A technology is provided for automated tuning of a machine learning model in a computing service environment. Predictive weights that include false positive outcomes, false negative outcomes, true positive outcomes, and true negative outcomes may be defined and/or received. A weight adjusted classification threshold, for use in a classification model of the machine learning model in a service provider environment, according to the predictive weights to enable the machine learning model to increase the total value of the machine learning model and decrease performance outcome errors. The improved classification threshold may be adjusted according to a change in the predictive weights. A data point may be classified according to the weight adjusted classification threshold in the classification model.