Archives of Disease in Childhood

Associations between special educational needs and physical and mental health conditions in children and young people in England: a population-based cross-secti…

Objective Children and young people (CYP) with special educational needs (SENs) have an increased risk of psychopathology and ...

Predicting Airline Delays at Scale with Spark ML

A UC Berkeley team used Apache Spark ML to predict airline delays at scale, training models on millions of flight records and ...
IEEE

Optimizing Pumpkin Seed Variety Classification: A Logistic Regression Approach to Morphological Analysis

Abstract: This paper employs logistic regression to categorise pumpkin seeds into Urgup_Sivrisi and Cercevelik based on a sample morphological database of 2500 pumpkin seeds from Urgup and Karacaoren, ...
GitHub

15_multinomial_logistic_regression.md

We will use a dataset on high school students’ choice of academic program (general, academic, vocational) to illustrate the methods. Binary logistic regression ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Scientific Research Publishing

Maulina, M., Hiola, Y.P. and Alamudi, A. (2025) Performance Evaluation of Multinomial Logistic Regression, Random Forest, and XGBoost Methods in Data Classification. Journal of ...

ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...
Scientific Research Publishing

Sitompul, L.R., Nababan, A.A., Manihuruk, M.L., Ponsen, W.A. and Supriyandi, S. (2025) Comparison of XGBoost, Random Forest and Logistic Regression Algorithms in Stroke Disease ...

ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...