Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Recent prospective observational study conducted on 224 adult patients undergoing elective videolaryngoscopic intubations ...

Artificial intelligence models used to detect depression on social media are often biased and methodologically flawed, ...

Alibaba Cloud has developed a new cluster management system called Eigen+ that achieved a 36% improvement in memory ...

Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical logistic ...

FinRegLab today released new empirical research demonstrating that adopting machine learning techniques and incorporating ...

1 INTRODUCTION The main goal of this paper is to develop a credible dynamic model of the multiple trailers on a tractor system for the production logistics application i.e. logistic train. This ...

Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables.

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania. Design We analysed cross-sectional survey data from the 2022 Tanzania ...

Includes data preprocessing, EDA, feature engineering, model training (Logistic Regression, Random Forest, XGBoost), hyperparameter tuning, model comparison, SHAP-based interpretability, and business ...

These concepts are used in technical analysis to forecast security prices. However, since autoregressive models base their predictions only on past information, they implicitly assume that the ...