When clustering only by dummy variables that represent categorical variables, the simplest measure of similarity between two observations is called the
a. matching coefficient.
b. Jaccard's coefficient.
c. Euclidean distance.
d. antecedent.
a
RATIONALE: When clustering observations sole on the basis of categorical variables encoded as 0-1 (or dummy variables), a better measure of similarity between two observations can be achieved by counting the number of variables with matching values. The simplest overlap measure is called the matching coefficient. To avoid misstating similarity due to the absence of a feature, a similarity measure called Jaccard's coefficient does not count matching zero entries.
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