Scientific Research Publishing

Hahn, P.R., Murray, J.S. and Carvalho, C.M. (2020) Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion ...

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
Hosted on MSN

Build Logistic Regression from Scratch in Python with Ease

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Frontiers

Development and validation of a LASSO logistic regression based nomogram for predicting live births in women with polycystic ovary syndrome: a retrospective cohort study

Objective: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live ...
GitHub

regularization-hyperparameters

This is a classification model implementation using Random Forest and Logistic Regression in Python and Spark. Originally implemented via AWS EMR Clusters.
eWeek

What is Logistic Regression? A Comprehensive Guide

Gov. Gavin Newsom signs SB 243, the first US law setting child-safety rules for AI chatbots, from crisis redirects to transparency requirements. Hollywood pushes back against OpenAI’s Sora 2 as ...
IEEE

Logistic Regression and Statistical Regularization Techniques for Risk Classification of Coronary Artery Disease Using Cytokines transported by High Density Lipoproteins

Abstract: Coronary artery disease (CAD) is a leading cause of mortality in the world. It is important to be able to proactively assess the risk of the disease, using novel biomarkers like cytokines ...