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Unformatted text preview: sep_l sep_w pet_l pet_w 0.92259864 0.99091932 0.98372995 0.93528037 b. Plotting the average principal component scores for each of the three species of iris shows that the second principal component does indeed serve to help differentiate among species. The first principal component clearly separates 1 ( Iris setosa ) from 2 and 3 ( Iris versicolor and Iris virginica ). While the distinction is much less clear, the second principal component separates 2 ( Iris versicolor ) from 3 ( Iris virginica ). speci es set osa versi col vi rgi ni c meanp20. 60. 50. 40. 30. 20. 1 0. 0 0. 1 0. 2 0. 3 meanp13 2 1 0 1 2 2. The condition index is essentially the square root of the ratio of the variances of the largest principal component to the smallest. In the presence of almost perfect collinearity in the data, the last principal component has almost zero variance, leading to a very large condition index....
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 Spring '08
 Staff
 Counting, Singular value decomposition, principal component, eigenface, Principal components analysis

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