QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

1 Department of Statistics, University of Sumer, Rifai, Iraq 2 Department of Statistics and Informatics Techniques, Northern Technical University, Mosul, Iraq In this paper, we considered a new study ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Objective: This study aimed to systematically identify risk factors for urinary catheter-related hematuria in patients with acute myocardial infarction (AMI). By integrating logistic regression and ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

This repository contains comprehensive implementations and solutions for statistical analysis, data science methodologies, and computational mathematics assignments. Each assignment demonstrates ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...

This cross-sectional study investigated SLD-related variables using decision tree regression in apparently healthy adults. Participants were consecutively recruited from the Health Promotion and Check ...