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 ...

A comparison of logistic functions. Logistic regression models have one dependent variable and several independent categorical or continuous predictor variables. Unlike standard linear regression ...

Regression models predict outcomes like housing prices ... might be predicted using multiple linear regression. Logistic regression. In logistics regression, you can use machine learning to ...

The main distinction between different types of regression model is that they are used for different types of outcome (eg, linear regression for a continuous outcomes and a logistic regression for a ...

When presented with a binary classification problem, a common strategy is to try probit or logistic regression first. If the resulting model is not satisfactory then you can try a neural model and use ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...