We have a 1-dimensional data set with 10 records, where x is the attribute and y...
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We have a 1-dimensional data set with 10 records, where x is the attribute and y is the target class. Attribute x takes values with 0.1 increments, from 0.1 to 1. Target class y takes two possible values, -1 and 1. Suppose we are applying the AdaBoost algorithm to create an Ensemble classifier that predicts a value for y, when inputted a value of x. The algorithm runs for 5 rounds and generates base classifiers C₁, C2, C3, C4, C5 with error rates of 0.04, 0.02, 0.01, 0.001, 0.00001, respectively. Corresponding classification results for each round are given in the following table: Round 1 2 3 4 5 x = .1 x = .2 -1 -1 1 1 -1 -1 -1 -1 -1 -1 x = .3 x = .4 -1 -1 -1 1 -1 1 -1 -1 1 -1 x = .5 -1 1 -1 -1 1 x = .6 -1 1 1 -1 1 x = .7 x = 1 -1 1 1 1 1 -1 -1 -1 1 ∞ x = .9 -1 1 1 1 -1 x = 1 -1 1 1 1 1 = What would be the predictions of the resulting ensemble classifier for a test set of x {0.3, 0.5, 0.7, 0.9}? Show all your calculations. We have a 1-dimensional data set with 10 records, where x is the attribute and y is the target class. Attribute x takes values with 0.1 increments, from 0.1 to 1. Target class y takes two possible values, -1 and 1. Suppose we are applying the AdaBoost algorithm to create an Ensemble classifier that predicts a value for y, when inputted a value of x. The algorithm runs for 5 rounds and generates base classifiers C₁, C2, C3, C4, C5 with error rates of 0.04, 0.02, 0.01, 0.001, 0.00001, respectively. Corresponding classification results for each round are given in the following table: Round 1 2 3 4 5 x = .1 x = .2 -1 -1 1 1 -1 -1 -1 -1 -1 -1 x = .3 x = .4 -1 -1 -1 1 -1 1 -1 -1 1 -1 x = .5 -1 1 -1 -1 1 x = .6 -1 1 1 -1 1 x = .7 x = 1 -1 1 1 1 1 -1 -1 -1 1 ∞ x = .9 -1 1 1 1 -1 x = 1 -1 1 1 1 1 = What would be the predictions of the resulting ensemble classifier for a test set of x {0.3, 0.5, 0.7, 0.9}? Show all your calculations.
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Fixed Income Securities Valuation Risk and Risk Management
ISBN: 978-0470109106
1st edition
Authors: Pietro Veronesi
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