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The key difference between linear and logistic regression lies in their output and the function they use to achieve this. Linear regression outputs continuous values, which makes it suitable for ...
The logistic regression model takes the natural logarithm of the odds as a regression function of the predictors. With 1 predictor, X, this takes the form ln[odds(Y=1)]=β 0 +β 1 X, where ln stands for ...
Explore the fundamental differences between linear and logistic regression in data science, including when and how to use each model effectively. Skip to main content LinkedIn Articles ...
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