Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
blockchain

NVIDIA cuTile Python Guide Shows 90% cuBLAS Performance for Matrix Ops

NVIDIA releases detailed cuTile Python tutorial for Blackwell GPUs, demonstrating matrix multiplication achieving over 90% of cuBLAS performance with simplified code. NVIDIA has published a ...
Frontiers

In-house chromogenic anti-factor Xa assay: development, validation, and identification of factors predicting APTT discordance

Background: Activated partial thromboplastin time (APTT) is the conventional test for monitoring unfractionated heparin (UFH) therapy, but discordance with anti-factor Xa results frequently occurs in ...
Hosted on MSN

Build logistic regression in Python from scratch easily

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
Bloomberg L.P.

Why Traditional Risk Models Overstate Factor Risk

Yes, I would like to be contacted by a representative to learn more about Bloomberg's solutions and services. By submitting this information, I agree to the privacy policy and to learn more about ...
GitHub

Docs: Incorrect FP/FN definitions in the Confusion Matrix explanation for Logistic Regression

First off, thank you for the excellent documentation on this project. It's been very helpful. I was studying the Logistic Regression section, specifically the part ...
GitHub

sayanaraj/task4-logistic-regression

The goal of this task is to build a binary classification model using Logistic Regression. The model is trained to predict a binary outcome (e.g., malignant vs benign tumors) using real-world data.
Scientific Research Publishing

Harrell, Jr. (2015) Regression Modeling Strategies with Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. 2nd Edition, Springer.

ABSTRACT: There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable ...
IEEE

Application of LDA and Multivariate Logistic Regression in Flood Forecasting and its AUC Evaluation

Abstract: This study combined linear discriminant analysis (LDA) and multivariate logistic regression models to systematically analyze key indicators in flood prediction, aiming to identify factors ...