Abstract: Interval-valued data are ubiquitous in fields such as finance and environmental monitoring. Forecasting such data is essential for uncertainty quantification, particularly in Air Quality ...

ABSTRACT: Variable selection using penalized estimation methods in quantile regression models is an important step in screening for relevant covariates. In this paper, we present a one-step estimation ...

Traffic incidents significantly disrupt freeway operations, causing delays, congestion, fuel waste, and economic losses. Effective incident management requires not only rapid detection and clearance ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

Survival models using EHR data predicted progression from NPDR or DME to PDR in type 2 diabetes patients. Key risk factors for progression included age, race, NPDR severity, and diabetic nephropathy.

This project explores confidence levels in cryptocurrency predictions using Ridge Regression, a regularized linear modeling approach that addresses multicollinearity among features. By analyzing ...

Since the rise of molecular high-throughput technologies, many diseases are now studied on multiple omics layers in parallel. Understanding the interplay between microRNAs (miRNA) and their target ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Abstract: The increasing integration of solar photovoltaic (PV) systems into modern energy grids presents significant challenges due to the intermittent and weather-dependent nature of solar energy ...

Institutional experience with pancreatic head versus body/tail cancer: A comparison of treatment outcomes. Preclinical study of safety and efficacy in vivo of a yttrium-90 resin microspheres glue ...