FEATURE SELECTION FOR RETRAINING CLASSIFIERS

摘要

A method of managing memory usage of a stored training set for classification includes calculating one or both of a first similarity metric and a second similarity metric. The first similarity metric is associated with a new training sample and existing training samples of a same class as the new training sample. The second similarity metric is associated with the new training sample and existing training samples of a different class than the new training sample. The method also includes selectively storing the new training sample in memory based on the first similarity metric, and/or the second similarity metric.

主权项

1. A method of managing memory usage of a stored training set for classification, comprising:
calculating at least one of a first similarity metric or a second similarity metric, wherein the first similarity metric is associated with a new training sample and existing training samples of a same class as the new training sample, and wherein the second similarity metric is associated with the new training sample and existing training samples of a different class than the new training sample; and selectively storing the new training sample in memory based at least in part on the at least one of the first similarity metric or the second similarity metric.