Question

what is Binomial logit model

What Is the Binomial Logit?

plz explain these two seprately

Answer 1

Q. What is Binomial logit model.

Ans.- The logit model, better known as Logistic Regression is a binomial regression model. Logit Model is used to associate with a vector of random variables to a binomial random variable. The logit model is a special case of a generalized linear model. It is widely used in machine learning.

Used:- The Binomial logit model uses something called the cumulative distribution function of the logistic distribution.

Explanation of Binomial Logit Model

We denote Y as the variable to predict and X=(x₁, x₂, ....., x_n) as predictive variables. In the context of the binomial logit model, the variable Y takes two possible modalities {1,0} the variables x_j are exclusively continuous or binary.

P(Y=1) denotes the probability that the variable Y takes the value 1. Similarly, we can define P(Y=0) as the probability that the variable Y takes the value 0. P(X|1) is the conditional distribution of X knowing the value taken by Y. Similarly, P(X|0) is defined.

The posterior probability of obtaining the modality 1 of Y knowing the value taken by X is noted P(1|X). Similarly, P(0|X) is defined.

Q. What is the Binomial Logit?

Ans:- A binomial logit predicts the probability that an observation falls into one of two categories of a dichotomous dependent variable based on one or more independent variables that can be either continuous or categorical. In statistics, the Binomial Logit is used to model the probability of a certain class or event existing such as pass/fail, win/lose. This can be extended to model several classes of events such as determining whether an image contains a cat, dog, lion, etc.