Related Questions:
– What is Logistic Regression?
– What is the Loss function for Logistic Regression?
– What are the major assumptions of logistic regression?
Logistic regression is a classification algorithm used to predict the probability of a binary or categorical outcome based on one or more independent variables. The algorithm learns a linear relationship from the input dataset and applies a non-linear transformation through the use of the Sigmoid function. The advantages and disadvantages of logistic regression are presented below.
Advantages of Logistic Regression:
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Disadvantages of Logistic Regression:
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Video Explanation
The following video from Data Unite walks through the advantages and disadvantages of Logistic Regression (Initial 2:20m of the video focuses on Advantages/Disadvantages) :
