GitHub

Aatish2006/iris_flower_classification

Project Scope Build a clean, modular machine-learning pipeline to classify Iris species using feature engineering, preprocessing, logistic regression, and evaluation artifacts.
GitHub

RMLR: Extending Multinomial Logistic Regression into General Geometries

This is the official code for our NeurIPS 2024 publication: RMLR: Extending Multinomial Logistic Regression into General Geometries.
Frontiers

Blockchain in Jordanian construction: an exploratory empirical study of stakeholder priorities and bootstrapped ROI

The full Colab notebook implementing the data cleaning, chi-square tests, multinomial and binary logistic regressions, and ROI bootstrapping. CSV files containing intermediate and final analysis ...
Frontiers

Bayesian outcome-specific ensemble modeling for football outcome prediction

Our three-level multinomial logistic framework, trained separately for each possible outcome and combined through a principled normalization procedure, was evaluated on held-out data. The framework ...
The Lancet

Prediction of hypertension and restenosis under guideline-directed management in aortic coarctation: development and validation of machine-learning models

aInstitute of Computer-Assisted Cardiovascular Medicine, Deutsches Herzzentrum der Charité Augustenburger Platz 1, 13353 Berlin, Germany bDepartment of Congenital Heart Disease – Pediatric Cardiology, ...