Dr. James McCaffrey of Microsoft Research kicks off a series of four articles that present a complete end-to-end production-quality example of binary classification using a PyTorch neural network, ...

Error-Correcting Output Codes (ECOC) provide a robust framework for decomposing multi-class classification challenges into multiple binary sub-problems. By constructing a codematrix that assigns ...

The likelihood ratio classification rule is derived from the location model, applicable when the data contains both binary and continuous variables. A method is proposed for estimating the rule in ...

In this study, we consider the binary classification problem for massive data based on a linear discriminant analysis (LDA) in a distributed learning framework. The classical centralized LDA requires ...

Among other things, this includes the ability to trace code from source to binary packages across both platforms, single sign-on support and unified project structures, including role mapping.