Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...
Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
GitHub

CheeseThuong/Predicting-water-levels-using-Linear-Regression

This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
IEEE

Comparing Logistic Regression Algorithm with K-Nearest Neighbor Algorithm to Extract Features from Images for Prescriptive Analysis of Mushroom Contamination

Abstract: In this project, we aimed to assess mushroom contamination by analyzing images using two different algorithms: a novel K-Nearest Neighbour algorithm and a traditional Logistic Regression ...
United States Army

Sustainment Proactivity: Using Data-Centric C2 to Predict Convoy Failures

Introduction You are tasked to lead a 40-truck convoy resupplying combat troops at the front during large-scale combat ...
IEEE

Analysis of Social Media Addiction: A Comparison of the Performance of Linear Regression and Random Forest Algorithms in Predicting User Behaviour

Abstract: Technology is developing rapidly, and one of the impacts felt from technology is the use of social media. Social media has become an inseparable part of people's lives. In the use of social ...