Machine Learning for Classification: Quadratic Discriminant Analysis vs Logistic Regression

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Welcome to the ultimate face-off in the realm of machine learning! In one corner, we have Quadratic Discriminant Analysis (QDA), a method that sounds like it’s straight out of a sci-fi movie.

And in the other corner, we have Logistic Regression, the tried and true champion of classification.

Get ready to witness the clash of these titans as we dive into the captivating world of machine learning for classification. Prepare to be enthralled as we unravel the strengths, weaknesses, and real-world applications of QDA and Logistic Regression. Let the battle begin!

How did I hear about this lad ‘QDA’?

While exploring the realm of Applied Machine Learning, I stumbled upon a treasure trove of knowledge called “Introduction to Statistical Learning with Applications in R” (Now in Python).

ISLP: Download it for free here

As I delved into its pages, I encountered a term that piqued my curiosity: Quadratic Discriminant Analysis (QDA). Surprisingly, QDA seemed to fly under the radar, rarely mentioned in the same breath as popular models like…