Classification in Python | logistic regression, LDA, QDA | Data Science With Marco

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📚 Theory: 0:00 - 7:07
🐍 Code: 7:08 - 26:36

In this video, we cover the topic of classification in data science. We learn about logistic regression, linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA), and use these algorithms to build a classifier for edible or poisonous mushrooms in Python.

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Really enjoying your videos so far. Really clear and great code. Thanks for putting them together. A few suggestions for this one: 1) cover what to do if target class is imbalanced 2) pick a different target that doesn't produce a perfect ROC/AUC so we can actually see how different models perform. Keep up the great work!

camerongridley

hey, can you show a case study where LDA is used over logistic regression or explain when to use one over the other?

saswatprusty

Thanks for the detail video, can you tell us how to test the assumptions for LDA and QDA using python

priyadoesdatascience

how do you set y_pred_lda = np.where(np.where(y_prob_lda > .5, 1, 0) if you have more than two classifications?

rablaze

good video, still didnt use cross validation did you? You imported it but didnt use it right?

pedroribeiro

Hallo, can you make a video about resampling methods (bootstrap, cross validation

moak

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