This project aims to predict house prices using the Ames Housing dataset. The goal is to preprocess the data, train a stacking model with multiple base models, and ...

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes. APLR builds predictive, interpretable ...

Abstract: The coronavirus pandemic made it clear that trustworthy ways are needed to take exams online for students. This report is about a way to monitor students take exams online using artificial ...

Abstract: The growing electricity demand and increasing penetration of Distributed Energy Resources are reshaping modern power systems, requiring more advanced strategies for network planning and ...

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 ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Polygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are estimated by the linear regression ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...