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- 1. Multiple Choice
Which system requires more entropy to be described?
Tossing a fair coin
Tossing a biased coin
- 2. Multiple Choice
Is it possible to test the same attribute twice along the same path on a decision tree for a categorical problem?
Yes
No
- 3. Multiple Choice
Is it possible that the same attribute will get selected twice in an ordinal or real-valued problem?
Yes
No
- 4. Multiple Choice
Decision trees are an algorithm for which machine learning task?
Clustering
Classification
Classification and Regression
Dimensionality reduction
Regression
- 5. Multiple Choice
When a tree is significantly deep, what does it indicate?
The samples have a large number of attributes
The dataset is possibly noisy
The tree under-fits the training data
None of these
- 6. Multiple Choice
Which of the following is true:
Deeper trees will always improve performance on the training data
Deeper trees will always improve performance when testing the model on unseen data
If a deeper tree improves performance on the training data, then it will also improve performance on new unseen data
- 7. Multiple Choice
For a binary classification problem with a balanced dataset, if one feature completely determines the class for each observation, what is the information gain from using this feature as the first node in a tree?
0
0.5
1
Not enough information
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