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Logistic Regression
Logistic Regression

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!!! Overview
[{$pagename}] is used in [Supervised Learning] and intended for [binary] [classification] problems to predict the probability of an instance belonging to the default class, when the [Predictor variable] is numeric or continuous.
[{$pagename}] is a [classification algorithm] that uses the properties of the [logistic function] in which, typically, [Weights] are assigned to [features] and then fed to the [logistic function], which outputs a number between 0 and 1. The decision boundary determines the classification.
[{$pagename}] can be extended to data with more than two categories which is referred to as [multinomial logistic regression]
[{$pagename}] requires proper [Training dataset] and properly tuned [Cost function] to be accurate.
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop