Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...
Objective This study aimed to evaluate the prevalence and predictors of cardiovascular disease (CVD), chronic kidney disease ...
If you like D-FINE, please give us a ⭐! Your support motivates us to keep improving! D-FINE is a powerful real-time object detector that redefines the bounding box regression task in DETRs as ...
A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...
Partial Least Squares Regression Trees for Multivariate Response Data With Multicollinear Predictors
Abstract: Some problems arise in analyzing massive complex data consisting of multivariate response variables and a large number of multicollinear predictor variables, especially when the sample sizes ...
This project aims to predict house prices using the Ames Housing dataset. The goal is to preprocess the data, train a stacking model with multiple base models, and ...
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