Multinomial logit - Wikipedia, the free encyclopedia
ثبت نشده
چکیده
In statistics, a multinomial logit (MNL) model, also known as multinomial logistic regression, is a regression model which generalizes logistic regression by allowing more than two discrete outcomes.[1] 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. Regression analysis
منابع مشابه
Vermiculite - Wikipedia, the free encyclopedia
It typically occurs as an alteration product at the contact between felsic and mafic or ultramafic rocks such as pyroxenites and dunites. It also occurs in carbonatites and metamorphosed magenesium rich limestone. Associated mineral phases include: corundum, apatite, serpentine and talc. It occurs interlayered with chlorite, biotite and phlogopite.[2] Vermiculite Wikipedia, the free encyclopedi...
متن کاملOn Rank-Ordered Nested Multinomial Logit Model and D-Optimal Design for this Model
In contrast to the classical discrete choice experiment, the respondent in a rank-order discrete choice experiment, is asked to rank a number of alternatives instead of the preferred one. In this paper, we study the information matrix of a rank order nested multinomial logit model (RO.NMNL) and introduce local D-optimality criterion, then we obtain Locally D-optimal design for RO.NMNL models in...
متن کامل