Text as Data (H) - Lecture 07 Quiz
1.
Sports - 4/100
Not sports - 27/1000
Sports - 28/55
Not sports - 108/10000
2. You are asked to build a supervised learning technique to identify all of the objects present in a picture. Is this:
regression
binary classification
single-label multi-class classification
multi-label multi-class classification
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?
To reduce floating point operations
So the non-occurrence of a term does not result in 0 probability
So that our numbers round easily to nice fractions
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