Glucose-to-potassium ratio shows a J-shaped link with AKI after traumatic brain injury, with high levels predicting increased ...

Abstract: In this project, we aimed to assess mushroom contamination by analyzing images using two different algorithms: a novel K-Nearest Neighbour algorithm and a traditional Logistic Regression ...

1 School of Artificial Intelligence and Information Engineering, Zhejiang University of Science and Technology, Hangzhou, China. 2 School of Sciences, Zhejiang University of Science and Technology, ...

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

Abstract: This research aims to compare the performance of Logistic Regression and Random Forest algorithms in classifying cyber-attack types. Using a data set consisting of 494,021 data points with ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...