Multinomial logistic regression

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Multinomial Logistic Regression is the linear regression analysis to conduct when the dependent variable is nominal with more than two levels.  Thus it is an extension of logistic regression, which analyzes dichotomous (binary) dependents

Multinomial regression is used to describe data and to explain the relationship between one dependent nominal variable and one or more continuous-level(interval or ratio scale) independent variables.

Multinomial logistic regression is known by a variety of other names, including polytomous LR, multiclass LR, softmax regression, multinomial logit, maximum entropy (MaxEnt) classifier, conditional maximum entropy model

Multinomial logistic regression is a particular solution to the classification problem that assumes that a linear combination of the observed features and some problem-specific parameters can be used to determine the probability of each particular outcome of the dependent variable. 

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