Logistic regression predictive models are also less prone to overfitting, which is when the number of observations exceeds the number of features. However, logistic regression also has some ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine ...

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 Data Science Lab How to Do Logistic Regression Using ML.NET Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET ...

We present a simple Bayesian logistic regression approach that uses a Laplace prior to avoid overfitting and produces sparse predictive models for text data. We apply this approach to a range of ...

Selection of a subset of meaningful covariates for a statistical model is an important and often time-consuming task in model building. Lawless and Singhal (1978, Biometrics 34, 318-327) proposed a ...