IEEE

Evaluation of Logistic Regression and Decision Tree Models for Lung Cancer Prediction Using Survey Data

Abstract: Lung cancer is one of the most deadly and ubiquitous forms of cancer globally. Early detection can make a significant difference in survival rates, prognosis, etc. Background The present ...
PNAS

Comparing variable selection and model averaging methods for logistic regression

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...
GitHub

plot_logistic_multinomial.py

Decision Boundaries of Multinomial and One-vs-Rest Logistic Regression This example compares decision boundaries of multinomial and one-vs-rest logistic regression on a 2D dataset with three classes.
GitHub

plot_sparse_logistic_regression_mnist.py

below what can be reached by an l2-penalized linear model or a non-linear multi-layer perceptron model on this dataset.
Nature

Risk stratification for postoperative complications after CRS and HIPEC in recurrent ovarian cancer patients: a comparative analysis of logistic regression and machine learning ...

Ovarian cancer (OC) remains one of the leading causes of gynaecological cancer mortality worldwide, with approximately 313,000 new cases and 207,000 deaths reported annually 1. Despite advances in ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
The Motley Fool

What Is a Statistical Model? Overview and Example

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...
Beebom

How to Access Claude 3 API for Opus and Sonnet Models (With Examples)

Anthropic is offering $5 worth of free API access to users and developers. You can start using the API for Opus and Sonnet models. However, API access for the smallest Haiku model is not available yet ...
Nature

Using large language models to suggest informative prior distributions in Bayesian regression analysis

Selecting prior distributions in Bayesian regression analysis is a challenging task. Even if knowledge already exists, gathering this information and translating it into informative prior ...
Medical News Today

Social model of disability: Meaning and examples

The social model of disability frames disability as something that is created by society, rather than only by medical conditions or physical differences. The model acknowledges that people have ...
IEEE

Maximum Likelihood for Logistic Regression Model With Incomplete and Hybrid-Type Covariates

Abstract: Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings ...
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 ...