c-lasso is a Python package that enables sparse and robust linear regression and classification with linear equality constraints on the model parameters. For detailed info, one can check the ...

Abstract: In multi-dimensional classification, the semantics of objects are characterized by multiple class variables from different dimensions. To model the dependencies among class variables, one ...

Section 1. Purpose. Across the country, ideologues who deny the biological reality of sex have increasingly used legal and other socially coercive means to permit men to self-identify as women and ...

The basic principles required to solve classification tasks with neural networks are used as building blocks in more complicated deep learning problems such as object detection and instance ...

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...

Current debates over the fundamental nature of biological sex are not merely esoteric academic musings. They have direct implications for policy related to sex-based legal protections and medicine. It ...

Because machine learning with deep neural techniques has advanced quickly, our resident data scientist updates binary classification techniques and best practices based on experience over the past two ...

Abstract: We consider the binary classification problem of static and dynamic mixed data in this paper. Different from mixed categorical and numerical data, the dynamic variables in the new type of ...

Purpose: This study proposes an S-TextBLCNN model for the efficacy of traditional Chinese medicine (TCM) formula classification. This model uses deep learning to analyze the relationship between herb ...

Recently, Transformer-based deep learning models like GPT-3 have been getting a lot of attention in the machine learning world. These models excel at understanding semantic relationships, and they ...