I would like to identify _almost_ duplicated rows in a data frame. For
example, I might declare as duplicates pairs of rows that are alike at about
80% of their columns. When working with tens of thousands of rows and upwards
of 20 columns an iterative approach, testing all permutations, can be time
consuming.
Duplicated() with incomparables sounds like the ticket. But previous
discussion in this forum indicates that specifying an
incomparable value when using duplicated() on a data frame is not yet
implemented.
Any suggestions about how to implement this efficiently would be appreciated.
All data are numerical, and each datum could, for example, be reduced to a byte
representation in a string. A fuzzy matching approach with agrep() might be
possible.
Thanks.
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