## Multinomial Logit

In statistics, a **multinomial logistic regression** model, also known as **softmax regression** or **multinomial logit**, is a regression model which generalizes logistic regression by allowing more than two discrete outcomes. That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which may be real-valued, binary-valued, categorical-valued, etc.). The use of the term "multinomial" in the name arises from the common conflation between the categorical and multinomial distributions, as explained in the relevant articles. However, it should be kept in mind that the actual goal of the multinomial logit model is to predict categorical data.

Read more about Multinomial Logit.

### Some articles on multinomial logit:

**Multinomial Logit**

... In statistics and machine learning, random

**multinomial logit**(RMNL) is a technique for (multi-class) statistical classification using repeated

**multinomial logit**analyses via Leo Breiman's random forests ...

... to one of the standard formulations of the

**multinomial logit**... Here, instead of writing the

**logit**of the probabilities pi as a linear predictor, we separate the linear predictor into two, one for each of the two outcomes Note that two separate sets of regression ... This shows clearly how to generalize this formulation to more than two outcomes, as in

**multinomial logit**...

... IIA is a property of the

**multinomial logit**and the conditional

**logit**models in econometrics outcomes that could theoretically violate this IIA (such as the outcome of ... Generalized extreme value,

**multinomial**probit (also called conditional probit) and mixed

**logit**are alternative models for nominal outcomes which relax IIA, but these models often have ... The

**multinomial**probit model has as a disadvantage that it makes calculation of maximum likelihood infeasible for more than five alternatives as it ...

**Multinomial Logit**- Applications

... Random

**multinomial logit**models combine a random ensemble of

**multinomial logit**models for use as a classifier ...