However, the vast majority of machine learning binary classification algorithms use 0-1 encoding for the target variable, so it makes more sense to programmatically convert so that the 0-1 encoded ...

AdaBoost ("adaptive boosting") is a powerful machine learning technique for binary classification -- predicting a variable that has two possible values. This article presents a demo program that ...

The patent, issued on February 25, 2025, covers a novel method for analyzing binary software efficiently by leveraging machine learning to predict peak memory usage and dynamically allocate ...

In this paper we propose principal weighted support vector machines, a unified framework for linear and nonlinear sufficient dimension reduction in binary classification. Its asymptotic properties are ...