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 ...

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics ...

Abstract: Machine learning (ML) is ever more frequently used as a tool to ... In this article we propose the use of binary decision diagrams (BDDs) as an interpretable ML model. BDDs can be deemed as ...

To address these challenges, this work employs context-informed incremental learning (CIIL) in an unconstrained, velocity-based environment for regression-based myoelectric control. Two new adaptive ...

In the TN regression proposed by Stoudenmire [7], an optimization algorithm based on gradient descent was proposed for learning with squared losses. The learning algorithm using the gradient is ...