Analytic system for graphical interpretability of and improvement of machine learning models

Abstract

A computing device provides a cluster connectivity graph presented on a display to summarize machine learning model performance. A classification value is predicted is predicted for a response variable value of each observation vector using a trained model. Observation vectors are divided into overlapping data slices that are separately clustered using the predicted classification value to define a set of clusters. A number of observations in each cluster is computed. An accuracy measure is computed for each cluster based on the predicted classification value. A number of overlapping observations between each pair of clusters is computed. The cluster connectivity graph includes a node for each cluster. A size of each node is determined from the computed number of observations. A fill-pattern of each node is determined from the computed accuracy measure. A connector line between each pair of nodes is determined from the computed number of overlapping observations.