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

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Trump pulls US out of more than 30 UN bodies Lack of oil ...

Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...

Early Risk Signals: Credit Card Delinquency Watch - AI-powered predictive analytics for proactive credit risk management. Machine learning models (Random Forest & Gradient Boosting) analyze behavioral ...

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering ...

ABSTRACT: The surge of digital data in tourism, finance and consumer markets demands predictive models capable of handling volatility, nonlinear dynamics, and long-term dependencies, where traditional ...

1 Division of Diabetes, Metabolism and Endocrinology, Showa Medical University Fujigaoka Hospital, Yokohama, Japan 2 Division of Endocrinology and Metabolism, Department of Medicine, Jichi Medical ...

Background: This study aimed to explore whether a predictive model based on body composition and physical condition could estimate seasonal playing time in professional soccer players. Methods: 24 ...