weightederm is a scikit-learn-style package for fast and accurate offline change point detection and estimation (or data segmentation) in regression settings via weighted empirical risk minimization ...

Firth penalization reduces small-sample bias and produces finite estimates even when standard MLE fails due to (quasi-)complete separation or monotone likelihood. Standard maximum-likelihood logistic ...

Machine Learning for Planners and Project Controls: What Actually Works I’m a planner and project controls engineer who started learning machine learning last year—not because I wanted to become a ...

This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and ...

eDepartment of Health Metric Sciences, School of Medicine, University of Washington, Seattle, WA, USA fDepartment of Applied Mathematics, University of Washington, Seattle, WA, USA ...

The use of large language models (LLM) has recently gained popularity in diverse areas, including answering questions posted by patients as well as medical professionals. Seventy-five consecutive ...

Department of Computing & UKRI Centre for Doctoral Training in AI for Healthcare, Imperial College London, London SW7 2AZ, United Kingdom Department of Materials, Department of Bioengineering & ...

Dr. James McCaffrey of Microsoft Research says the main advantage of scikit is that it's easy to use (even though most classes have many constructor parameters). Logistic regression is a machine ...

a. I have been lucky to be in a position that I can have a positive impact on the career of hundreds (if not thousands) of people. Fortunately, I feel relatively secure in my career and I have ...

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally ...