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mlcourse.ai. Assignment #3 (demo)
Decision trees with a toy task and the UCI Adult dataset.
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3.1. What is the entropy S0 of the initial system? *
1 point
3.2. Let's split the data with a feature "Looks_handsome". What is the entropy S1 of the left group - the one with "Looks_handsome". What is the entropy S2 in the opposite group? What is information gain (IG) if we consider such a split? *
2 points
Required
3.3. What is the entropy of a state given by a list balls_left? *
2 points
3.4. What is the entropy of a fair dice? (where we look at a dice as a system with 6 equally probable states) *
1 point
3.5. What is the information gain of splitting the initial dataset into balls_left and balls_right? *
2 points
3.6. What is the test set accuracy of a decision tree with maximum tree depth of 3 and random_state = 17? *
1 point
3.7. What is the test set accuracy of a decision tree with maximum tree depth of 9 and random_state = 17? *
1 point
Do you have any remarks concerning the assignment? In case of apparent errors/typos please use GitHub Issues and/or Pull Requests (https://github.com/Yorko/mlcourse.ai).
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