TOPICS COVERED IN THIS LECTURE:

Part A: Binary logistic regression
Topic:  Classification, Binary logistic regression, Evaluation of binary outcomes (predictions, confusion matrix, ROC curve, loss functions), Data imbalance.
Script: lesson3A.R 

Part B: Advanced methods for logistic regression
Topic:   Regularized logistic regression, Bagging, Tree-based methods: classification trees, Bagging decision trees, Random decision forest.
Script:  lesson3B.R  

SCRIPTS:

PRESENTATION:

MIDTERM:

Find the assignment and dataset here:

Here, you will upload your scripts:

Deadline 10.12. 23:59!!

FINAL EXAM:

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(choose the folder with today's date)

Please upload your solutions here: