Logistic Regression
Algorithm learns a function that divides the data into two parts. It is used to solve classification problems.
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Formal definition
In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place. In machine learning the idea is estimating the parameters of a logistic function.
Intuition
In statistical learning (as a part of machine learning) it is all about finding boundaries in data. For instance, in a binary classification problem (classify between
two classes) the logistic regression algorithm finds a boundary with the highest likelihood of identifying a class on both sides.

Formal definition
In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place. In machine learning the idea is estimating the parameters of a logistic function.
Intuition
In statistical learning (as a part of machine learning) it is all about finding boundaries in data. For instance, in a binary classification problem (classify between
two classes) the logistic regression algorithm finds a boundary with the highest likelihood of identifying a class on both sides.
Updated on: 13/10/2022
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