MACHINE LEARNING: BASICS FOR BEGINNERS: FAST AND EASY WAY TO LEARN CODING BASICS by TAM JP

Author:TAM, JP [TAM, JP]
Language: eng
Format: epub
Published: 2020-03-08T16:00:00+00:00

Assumptions in Logistic Regression

In binary logistic regression, the target should be binary, and the result is denoted by the factor level 1.

The independent variables should be independent of each other, in a sense that there should not be any multi-collinearity in the models.

Only meaningful variables should be included in the model.

For a logistic regression model, large sample size to be included

Binary Logistic Regression Model

It is one of the simpler logistic regression models in which the dependent variables are in two forms; either 1 or 0. It models a relationship between multiple predictor/independent variables and a binary dependent variable in order to discover the finest suitable model. It calculates the probability of an occurring event by the best-fitted data to the logit function. In this the linear function is used to feed as input to the other function, which is mathematically given as;

y = b0 +b1 x

Now apply the sigmoid function to the line;

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