(f) Given a vector of real numbers, if a raw number in the vector is smaller than the mean, its corresponding normalized value will be negative after z-score standardization. (g) Given any two vectors of the same length, the L2 distance between them is always smaller than or equal to the L₁ distance between them. (h) The covariance matrix (of one random vector) has square shape. (i) Let Р and 9 be two different distributions. The KL divergence between p and q is the same as the KL divergence between q and p. (j) Principal Component Analysis (PCA) can generate new features.

(f) Given a vector of real numbers, if a raw number in the vector is smaller than the mean, its corresponding normalized value will be negative after z-score standardization. (g) Given any two vectors of the same length, the L2 distance between them is always smaller than or equal to the L₁ distance between them. (h) The covariance matrix (of one random vector) has square shape. (i) Let Р and 9 be two different distributions. The KL divergence between p and q is the same as the KL divergence between q and p. (j) Principal Component Analysis (PCA) can generate new features.

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter12: Review Of Calculus And Probability

Section: Chapter Questions

Problem 4RP

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