Abstract: This research paper aims to predict house prices with more efficiency and accuracy. The research paper involves three machine learning algorithms, "linear regression, lasso regression, and ...

Gophen, M. and Peres, M. (2026) Chill Hours Record: A Sensitive Method for Climate Change Indication. Open Journal of Modern ...

TabPFGen is a Python library for generating high-quality synthetic tabular data using energy-based modeling and stochastic gradient Langevin dynamics (SGLD). It supports both classification and ...

A large U.S. firefighter cohort study identified personal, occupational, and department-level predictors of serum PFAS concentrations, highlighting both modifiable exposures and persistent background ...

On January 23, tens of thousands of Minnesotans braved subzero temperatures and took to the streets as part of a call for ...

Predictors of Opioid Use among Active-Duty Soldiers Following Postoperative Prescription. Pain Studies and Treatment, 14, ...

Objectives To examine how the population composition, practice organisation and geographical context of general practice clinics are associated with unwarranted variation in prescribing patterns ...

Introduction Duplicate medical records occur when a single patient is assigned multiple medical record numbers within an ...

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

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

Patients with depressive symptoms and asthma had elevated levels of serum brain-derived neurotrophic factor in association ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...