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