logistic regression, or logit regression, is a type of probabilistic statistical classification model. It is also used to predict a binary response from a binary predictor, used for predicting the outcome of a categorical dependent variable (i.e., a class label) based on one or more predictor variables (features).

The following matlab project contains the source code and matlab examples used for logistic regression.

The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.

## Project Files:

Four parameters logistic regression there and back again in matlab

Distributed logistic regression using expectation propagation. in matlab

Three parameters logistic regression there and back again in matlab

Five parameters logistic regression there and back again in matlab

This script shows how to perform an univariate logistic regression in matlab.

Logistic regression with regularization used to classify hand written digits in matlab

Logistic regression with regularization used to classify hand written digits in matlab

New regression capabilities in r2012a in matlab

Glmlab is a set of m-files for using matlab for analysing generalised linear models.

Fitting with matlab statistics, optimization, and curve fitting

Boosted generalized additive models (bgam) package in matlab

Hot to run weka classifiers within matlab

Accelerated failure time (aft) models in matlab

Online batch generalized linear models under square loss in matlab

Fit glm with quadratic penalty in matlab

Restricted cubic spline in matlab

Confusion matrix 3d with overall pcc and group statistics in matlab