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Principal components are artificial variates designed to maximize variance accounted for, not designed for interpretability. True...

Principal components are artificial variates designed to maximize variance accounted for, not designed for interpretability.

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Answer #1

Solution: True

  • First principal component captures the maximum variance in the data set and determines the direction of highest variability in the data. Larger the variability captured in first component, larger the information captured by component.
  • Second principal component also captures the remaining variance in the data set and is uncorrelated with first component. In other words, the correlation between first and second component should is zero.
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