Logistic regression can be thought of as an extension to, or a special case of, linear regression. If the outcome variable is a continuous variable, linear regression is more suitable.

Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data ...

We apply an alternative statistical method, logistic regression, to estimate the strength of selection on multiple phenotypic traits. First, we argue that the logistic regression model is more ...

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