Estimate the jaccard similarity correctly

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Reference no: EM131220907

One might expect that we could estimate the Jaccard similarity of columns without using all possible permutations of rows. For example, we could only allow cyclic permutations; i.e., start at a randomly chosen row r, which becomes the first in the order, followed by rows r + 1, r + 2, and so on, down to the last row, and then continuing with the first row, second row, and so on, down to row r - 1. There are only n such permutations if there are n rows. However, these permutations are not sufficient to estimate the Jaccard similarity correctly. Give an example of a two-column matrix where averaging over all the cyclic permutations does not give the Jaccard similarity.

Reference no: EM131220907

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