Questionnaire 8

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Questionnaire 8

Open until 30.5.23, 08:00

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Given the following samples shown below from 3 different distributions along r1 and r2 axes and assuming that v1 and v2 are the variance along the first two principle components: which of the samples has the largest ratio v2/v1?

20 points

sample a

sample b

sample c

non of the above

Which of the following steps *isn't* important when implementing PCA?

20 points

centering the covariance matrix

scaling the covariance matrix

diagonalizing the covariance matrix

pre-defining number of principle components

The covariance of two random variables (X & Y) is zero and their variance is non-zero. John claims that PCA on the two variables will probably yield only one non-zero principle component. Is that true?

20 points

Yes

Not enough information to determine

Only if the two variables are Gaussian distributed

ICA algorithm isn’t aimed to maximize the following feature:

20 points

high moments of the data

mutual information

variance of the data

independency of the components

Which of the following steps would perform better for reducing dimensions of a data set?

20 points

removing columns which have too many missing values

removing columns which have high variance in the data

removing columns with dissimilar data trends

none of these

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