Linear regression is a type of supervised machine learning algorithm that is used to model the linear relationship between a dependent variable (in this case, earthquake magnitude) and one or more ...

Materials and methods: We compared traditional logistic regression (LR) with five ML algorithms LR with Elastic-Net, Random Forest (RF), XGBoost (XGB), Support Vector Machine, Deep Learning, and an ...

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric ... multicenter, case-control study. A diagram demonstrating overall study design and analytic pipeline is depicted ...

Training a machine learning model. ... Linear regression. To train a machine to ... find the features that contribute most meaningfully to your prediction output. As shown in the diagrams, ...

Methods: Using the administrative health data of people with IBD who died between 2010 and 2020 in Ontario, Canada, we conducted a population-based, retrospective cohort study. We described the ...

Welcome to our Flask API-based Machine Learning model, designed as a comprehensive Recommendation and Prediction System. Today, I'm excited to present this one-screen dashboard that exemplifies our ...

The XGBoost machine learning algorithm was used to build an infection prediction model for NDMM patients with easy operation and good performance with an AUC of 0.884. This model can help determine ...

A wide range of machine learning algorithms such as linear regression, logistic regression, support vector machine, and kernel methods, neural networks, and many others are available for the learning ...