Unformatted text preview: e list in Part A. Remember to only use the
classifiers you circled in Part B.
Round 1 Round 2 Round 3 w1
α Part D (10 points)
What is the final classifier you find when performing three rounds of Boosting: How many of the data points does your final classifier classify correctly? 9 Part E (10 points)
Wesley Windham-Pryce, a fellow consultant, has noticed a few correlations between some of the
classifiers you used, and so he suggests using a new set of weak classifiers consisting of each pair of
your original weak classifiers logically ANDed or ORed together (so for instance, two of the new
classifiers would be "Emo=Y OR Evil=Y" and "Sparkly=N AND Transforms=Y"). He believes that
you will be able to classify large vampire datasets more quickly and with fewer rounds of boosting
using his system. Do you agree or disagree with Wesley? Explain your argument briefly and
precisely. 10 Tear off sheet—you need not hand this in. ID Name Vampire Evil Emo Transforms Sparkly # Romantic
Interests ID 1 Dracula Y Y N Y N 5 1 2 Angel Y N Y Y N 5 2 3 Edward Cullen Y N Y N Y 1 3 4 Saya Otonashi Y N Y N N 3 4 5 Lestat
de Lioncourt Y N Y N N 5 5 6 Bianca St.
Claire Y Y N Y N 5 6 7 Mircalla
Karnstein Y Y N Y N 5 7 8 Sailor Moon N N N Y Y 1 8 9 Squall
Leonhart N N Y N N 1 9 N N N N N 5 10 10 Circe 11 0.2 0.1 M M H F 0.7 T 0.8 V V H Z R M Z F F 0.01 F T 0.4 T F 0.5 T 12 V T 0.6 R F 0.1 T 0.3...
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- Fall '10
- Artificial Intelligence, Bayesian probability, Bayesian network, Abraham Van Helsing, Randall Davis, final numeric answer