Optimal data partition for semi-automated labeling

Abstract

In a pattern recognition sequence consisting of alternating steps of interactive labeling, classifier training, and automated labeling (e.g., CAVIAR systems), the choice of sample size at each step affects the overall amount of human interaction necessary to label all the samples correctly. The appropriate splits depend on the error rate of the classifier… (More)

Topics

5 Figures and Tables

Slides referencing similar topics