Devdiscourse

Stacked AI model improves credit default forecasting

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...
Frontiers

A clinical prediction model for delirium tremens: development and validation in alcohol-dependent patients using multivariable logistic regression

Delirium tremens (DT) is a severe complication of alcohol withdrawal. This study aimed to develop and validate a prediction model for DT risk in hospitalized patients with alcohol dependence, using ...
IEEE

A Logistic Regression Based Credit Risk Assessment Using WoE Bining and Enhanced Feature Engineering Approach ANOVA and Chi-Square

Abstract: This research paper presents a comprehensive approach to build a data-driven credit risk model using machine learning techniques. Despite advancements in risk assessment methods, loan ...
IEEE

Research on Tennis Match Momentum Prediction Based on Logistic Regression and GBDT Model

Abstract: Tennis is a complex sport where shifts in match momentum can dramatically alter the outcome of games. This paper aims to predict changes in momentum during tennis matches using Logistic ...