IEEE

Segmenting and Predicting Consumer behavior in cosmetic industry: A Machine learning approach using Latent class and Random Forest techniques

Abstract: The proposed study examines consumer purchasing behavior using the Latent Class Choice Models (LCCM) to determine the significant elements that impact purchase decisions. An online survey, ...
Under30CEO on MSN

Analytics that move the needle: Sohan Sethi shapes cost, efficiency, and scale

The healthcare industry is at a crossroads. Advanced analytical technology and operational efficacy converge with strategic ...
Frontiers

Metaheuristic-based gallstone classification using rotational forest explained with SHAP

1 Electronics and Communication Engineering Discipline, Khulna University, Khulna, Bangladesh 2 Centre for Wireless Technology, CoE for Intelligent Network, Faculty of Artificial Intelligence and ...
Yardbarker

Predicting North Carolina's Top Performances Against Wake Forest

It has been a week since the North Carolina Tar Heels last suited up, which resulted in a 97-83 loss to the SMU Mustangs at the Moody Coliseum. That feeling of disappointment has been brewing, and the ...
IEEE

Predicting Social Media Virality Using Stacking Ensemble with Random Forest, XGBoost and Logistic Regression

Abstract: The research investigates predicting the virality of content on social media platforms using a stacking ensemble model with Random Forest, XGBoost, and Logistic Regression. Social media ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...