Text as Data (H) - Lecture 07 Quiz
1.
Not sports - 108/10000
Sports - 28/55
Sports - 4/100
Not sports - 27/1000
2. You are asked to build a supervised learning technique to identify all of the objects present in a picture. Is this:
multi-label multi-class classification
regression
single-label multi-class classification
binary classification
3. Which classifier is infinitely flexible, able to fit to any features?
None of the above
Decision Tree
Naive bayes
Logistic Regression
4. In picking the next decision point, a decision trees picks the feature that
best discriminates between the classes
balances the classes across the decision
5. Why is smoothing used in Naive Bayes?
So that our numbers round easily to nice fractions
So the non-occurrence of a term does not result in 0 probability
To reduce floating point operations
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