CS404FinalExam-121505_1

# CS404FinalExam-121505_1 - Use the algorithm below for the...

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1. The StudentNumber would have more gain. This is because it will be able to split on each number for each student. I would use the height instead. This would still have a decent gain, but it would not split on every student, so the tree would still be meaningful and easier to read. 2. Keep the best expert Stepwise regression: Start with no variables Keep adding variables until no statistically significant improvement Principal Components Analysis 3. Binning – skipping 4. This was not discussed in the notes, the book or the class, skipping 5. a) D(9) = (-1.1 - 3)^2 + (-4.1 - 6)^2 + (0.1 - 4)^2 = 16.81+102.01+15.21=134.03 b) Assume that the nodes are in a grid layout, where each adjacent node is at a distance of one. If node 9 is the winner, update 8, and 6 as well.

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Unformatted text preview: Use the algorithm below for the update function for all nodes, where j is the node number, and i is the row of the vector. 6. 7. Similarity – they both attempt to minimize the sum of squared error when learning from data Difference – neural networks can predict non-linear models 8. Chi-Squared= (12-6.4)^2/6.4+(4-9.6)^2/9.6+(2-4)^2/4+(8-6)^2/6+(4-7.6)^2/7.6+(15-11.4)^2/11.4 9. x coordinate (percent false positives) = FP/ All Neg = 16/(65+16) = 19.75% y coordinate (percent true positives) = TP/All Pos = 82/(82+22)=78.85% Amount made =82 TP * 100 dollar reward = \$8200 Cost of campaign = 15 dollars * 185 total people = \$2775 Net profit = 8200 – 2775 = \$5425...
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## This note was uploaded on 08/25/2011 for the course CPE 404 taught by Professor Merz during the Fall '09 term at Missouri S&T.

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CS404FinalExam-121505_1 - Use the algorithm below for the...

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