Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

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 ...

I would like to contribute a lightweight and optimized implementation of Horizontal Federated Logistic Regression (2025 optimized version) to this project. This implementation is tailored for ...

In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a ...

Abstract: Machine learning models are being increasingly deployed in sensitive applications where data privacy and model security are of paramount importance. This paper introduces a novel ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

ABSTRACT: Earned Value Management (EVM) has emerged as an effective project monitoring and control method while the construction industry has lagged other industries, such as defense and aerospace, in ...

1 Clinical Laboratory, Dongyang People’s Hospital, Dongyang, Zhejiang, China 2 Clinical Laboratory, The Second People’s Hospital of Yuhuan City, Yuhuan, Zhejiang, China Introduction: In this study, we ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

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 ...

Abstract: We present a versatile GPU-based parallel version of Logistic Regression (LR), aiming to address the increasing demand for faster algorithms in binary classification due to large data sets.