Range-resident logistic model connects animal movement and population dynamics

Despite decades of independent progress in population ecology and movement ecology, researchers have lacked a theoretical bridge between these two disciplines. "Ecologists have been trying to ...
IEEE

PrivESD: A Privacy-Preserving Cloud-Edge Collaborative Logistic Regression Model Over Encrypted Streaming Data

Abstract: Outsourcing logistic regression classification services to the cloud is highly beneficial for streaming data. However, it raises critical privacy concerns for the input data and the training ...
IEEE

Secure and Efficient Logistic Regression With Secret-Sharing MPC and Differential Privacy

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 ...
Scientific Research Publishing

Mehta, C.R. and Patel, N.R. (1995) Exact Logistic Regression: Theory and Examples. Statistics in Medicine, 14, 2143-2160.

ABSTRACT: Introduction: Biopsy procedures represent an essential diagnostic tool in the management of oral lesions. This study aims to evaluate the knowledge, attitudes, and practices of dental ...
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 ...
Hosted on MSN

Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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 ...
Frontiers

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.