Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

Federated learning (FL) enables multi-institutional predictive modeling without sharing raw patient data, preserving privacy while leveraging diverse data sets. This study evaluates the use of linear ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

The XGBoost machine learning results for survival risk factor importance (Figure 4B) indicated that NPAR and SIRI had the most significant impact on the outcomes; similar findings were obtained from ...

Every year at this time, millions of college hoops fans–from the casuals to the fanatics–chime in with their picks ahead of the NCAA Tournament. Now that the brackets are set, the eternal ...

Are you interested in trying new food and exploring new places, but unsure where to start? This research uses machine learning to predict restaurant ratings. The article compares two options: simple ...

Johnson, M. and Lee, S. (2023) Comparative Analysis of Regression Models in Academic Performance Forecasting. International Journal of Machine Learning, 12, 78-92.

Here we propose a classical machine learning system, built around a Random Forest classifier paired with a novel feature extraction algorithm adapted from Explainable Boosted Linear Regression (EBLR).