Systems and methods for characteristic classification and object type classification using hyper-trained suites of machine learning models

Abstract

Described herein are systems and methods for generating multi-class machine learning classifiers using a plurality of hyper-trained binary classifiers to perform both characteristic detection and object type classification. A range associated with a characteristic of the data sought to be classified may be divided into a plurality of sub-ranges that can be ordered. A plurality of binary machine learning classifiers can be generated, with each binary classifier associated with one of the sub-ranges. Each binary classifier of the plurality of classifiers may be generated by training the classifier to determine if a given input data set contains a characteristic within or outside of the sub-range associated with the binary classifier. Once the binary classifiers have been trained, they can be used to determine what value within the range of the characteristic an input data sample has, and may be used to determine other properties about the input data.