JSTOR Daily

Label-Noise Resistant Logistic Regression for Functional Data Classification with an Application to Alzheimer's Disease Study

Alzheimer's disease (AD) is usually diagnosed by clinicians through cognitive and functional performance test with a potential risk of misdiagnosis. Since the progression of AD is known to cause ...
Visual Studio Magazine

Logistic Regression Using Python

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

A total of 737 treatment-naïve patients with CLL diagnosed at Mayo Clinic were included in this study. We compared predictive abilities for two survival models (Cox proportional hazards and random ...
technologynetworks

Logistic Regression

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
JSTOR Daily

Using Logistic Regression to Analyze the Sensitivity of PVA Models: A Comparison of Methods Based on African Wild Dog Models

We used logistic regression as a method of sensitivity analysis for a stochastic population viability analysis model of African wild dogs (Lycaon pictus) and compared these results with conventional ...