Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

This research presents deep ... learning automation as the novel approach for automatic OSA detection through polysomnographic assessments. Our proposed system implements Genetics Algorithm optimized ...

Q: What main themes of your chapter would you like readers to take away and bring back to their institutions and organizations? A: In my chapter, I ask whether the experience of the pandemic will help ...

James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning regression ...

The nature of such a “black box”, especially for deep learning ... and Architecture In this study, we will evaluate the effectiveness of several AI and ML models in credit risk assessment and compare ...

Chip development teams have long been clamoring for a better way to manage and debug regression loops. Recently, artificial intelligence (AI) using machine learning (ML) technology has become ...

Deep learning and artificial intelligence (AI) are rapidly evolving fields with new technologies emerging constantly. Five of the most promising emerging trends in this area include federated ...