Scientific Research Publishing

Wilson, D.L. (1994) The Analysis of Survival (Mortality) Data: Fitting Gompertz, Weibull, and Logistic Functions. Mechanisms of Ageing and Development, 74, 15-33.

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
Hosted on MSN

Logistic Regression Cost Function ¦ Machine Learning ¦ Simply Explained

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the model ...
Frontiers

Expectation-maximization alternating least squares for tensor network logistic regression

1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...
Scientific Research Publishing

Zaidi, A. and Al Luhayb, A.S.M. (2023) Two Statistical Approaches to Justify the Use of the Logistic Function in Binary Logistic Regression. Mathematical Problems in ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...
WEAU

Twins with rare genetic PKAN disease back in routine while dealing with regression on muscle function

EAU CLAIRE, Wis. (WEAU) - After more than a year the HSHS Hospital/Prevea Clinic closures were announced, a couple of Eau Claire County boys have gotten back in routine despite some set-backs. “I feel ...
IEEE

Learning Expert-Level Racing Strategies via Scheduled Cost Functions in Model Predictive Control

Abstract: In racing sports, driving strategies necessitate meticulous control and optimal utilization of vehicle dynamics. Model predictive control (MPC) has emerged as an effective approach for ...
Frontiers

Logistic regression model for predicting risk factors and contribution of cerebral microbleeds using renal function indicators

Background: The brain and kidneys share similar low-resistance microvascular structures, receiving blood at consistently high flow rates and thus, are vulnerable to blood pressure fluctuations. This ...