Why logistic regression called why not classifier called.

Question

Accepted Answer

Logistic regression is a type of classifier that uses a logistic function to model a binary dependent variable.

Logistic regression is a statistical method used to analyze a dataset in which there are one or more independent variables that determine an outcome.
It is called logistic regression because it uses a logistic function to model a binary dependent variable.
The logistic function is an S-shaped curve that can take any real-valued number and map it into a value between 0 and 1.
This makes it ideal for modeling probabilities, which are always between 0 and 1.
Logistic regression is commonly used in machine learning for binary classification problems, such as predicting whether a customer will buy a product or not.
It is also used in medical research to model the probability of a patient having a certain disease based on their symptoms and other factors.

Accepted Answer

The Value for logistic regression goes from -∞ to +∞, but we regress it in a small range of 0-1,therefore to maintain the heritage it is called as logistic regression and not logistic classifier

Why logistic regression called why not classifier called.

Top AlmaBetter Data Analyst interview questions & answers

Popular interview questions of Data Analyst