Contrivedness: The boundary between pattern recognition and numerology

Abstract The irreducible informational loss expended in a pattern search procedure is quantified using the concept of contrived entropy. In multivariate analysis this quantity is of value in distinguishing true patterns from statistical noise and in deciding to what depth a search procedure should be conducted. For a specific partition, the contrived entropy is defined as the partition entropy averaged over all possible permutations of event outcomes. The contrived entropy associated with a search procedure or set of attempted partitions is taken to be the expectation value of the minimized partition entropy for each permutation. The behavior of the contrived entropy is illustrated for a simple univariate case.

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