Stepwise regression predicts Arctic sea-ice extent with high accuracy

Under the influence of global warming, the Arctic is transitioning from a state dominated by multi-year thick ice to a "New ...
Veritasium on MSN

The Logistic Map That Exposed Chaos Hiding in Everyday Life

In the 1970s, mathematicians studying population growth discovered a simple equation — the logistic map — that produced ...
How-To Geek on MSN

How to run R-style linear regressions in Python the easy way

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...
Scientific Research Publishing

Tabaei, B.P. and Herman, W.H. (2002) A Multivariate Logistic Regression Equation to Screen for Diabetes. Diabetes Care, 25, 1999-2003.

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...
Frontiers

A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema

Purpose: To develop a machine learning model to predict anatomical response to anti-VEGF therapy in patients with diabetic macular edema (DME). Methods: This retrospective study included patients with ...
JSTOR Daily

The study on the early warning period of varicella outbreaks based on logistic differential equation model

Chickenpox is a common acute and highly contagious disease in childhood; moreover, there is currently no targeted treatment. Carrying out an early warning on chickenpox plays an important role in ...
Frontiers

Predicting distant metastasis of bladder cancer using multiple machine learning models: a study based on the SEER database with external validation

1 The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China 2 Department of Urology, Second Affiliated Hospital of Nanchang University, Nanchang, China Background ...
GitHub

ahmedjidar/ml-logistic-regression-20241001

The output variable must be either continuous nature or real value. The output variable has to be a discrete value. The regression algorithm’s task is mapping input value (x) with continuous output ...