Text as Data (H) - Lecture 07 Quiz
1.
Not sports - 27/1000
Not sports - 108/10000
Sports - 4/100
Sports - 28/55
2. You are asked to build a supervised learning technique to identify all of the objects present in a picture. Is this:
binary classification
multi-label multi-class classification
regression
single-label multi-class classification
3. Which classifier is infinitely flexible, able to fit to any features?
Decision Tree
None of the above
Naive bayes
Logistic Regression
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 that our numbers round easily to nice fractions
So the non-occurrence of a term does not result in 0 probability
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