I have a very large data set (over 60K rows), a subset of which for a particular data type is around 32K rows). Sample data using dput is given below (first 200 rows of Water). My question is, how can I use Jaccard distance from the proxy package to remove data in the data set that is say 95% similar and keep the remainder. Is there a way to use the output from the Jaccard distance function in the proxy package to do this?
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similarity<- proxy::dist(Water, by_rows = TRUE, method = "Jaccard")
I would like to be able to calculate the similarity between each row in the data set and then remove the ones that are too similar to each other. But being a very large data set, the methods I have seen on Stackoverflow wont work as R runs out of memory. I am hoping to be able to create a function that will use the similarity calculated using the jaccard distance to apply it to the data set and remove those rows that are within a given similarity. Any ideas how to do that would be much appreciated!
