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

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 ...

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

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 ...

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

Academy of Art and Design, Yancheng Teachers University, Yancheng, China Introduction: With the acceleration of global aging, the accurate prediction of care service demand for older adults is of ...

The Buffalo Bills haven't won in Houston since the J.P. Losman days, and that didn't change, dropping another one to the Texans, 23-19. The Texans' defense is No. 1 in the league for a reason, and ...

Introduction: Granulosa cell tumors (GCTs) of the ovary are rare malignancies with limited systemic treatment options and high recurrence rates. Combining tumor necrosis factor-related ...

According to a new study, the use of an artificial intelligence-based "You Only Look Once (YOLO)" algorithm showed high precision in detecting B lines on lung ultrasound (LUS) images, with substantial ...

This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...