Data mining using group classifiers

Abstract

In various examples, data mining using group classifiers for autonomous and semi-autonomous systems and applications is described. For instance, systems and methods may train and use a classifier that is configured to determine whether data samples (e.g., images) represent objects associated with a group in various training and/or mining iterations. For instance, after each iteration, the classifier may become more accurate such that the classifier is able to better identify first data samples that are associated with the group (e.g., positive images) and/or second data samples that are not associated with the group (e.g., negative images). Additionally, the systems and methods may use another classifier to determine classifications associated with objects represented by at least the first data samples that are associated with the group. The systems and method may then store these first data samples and the classifications in one or more databases.