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PORemove highly correlated variables
 

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    <p>I have a huge dataframe 5600 X 6592 and I want to remove any variables that are correlated to each other more than 0.99 I do know how to do this the long way, step by step i.e. forming a correlation matrix, rounding the values, removing similar ones and use the indexing to get my "reduced" data again.</p> <pre><code>cor(mydata) mydata &lt;- round(mydata,2) mydata &lt;- mydata[,!duplicated (mydata)] ## then do the indexing... </code></pre> <p>I would like to know if this could be done in short command, or some advanced function. I'm learning how to make use of the powerful tools in the R language, which avoids such long unnecessary commands</p> <p>I was thinking of something like</p> <pre><code>mydata &lt;- mydata[, which(apply(mydata, 2, function(x) !duplicated(round(cor(x),2))))] </code></pre> <p>Sorry I know the above command doesn't work, but I hope I would be able to do this.</p> <p>a play-data that applies to the question:</p> <pre><code>mydata &lt;- structure(list(V1 = c(1L, 2L, 5L, 4L, 366L, 65L, 43L, 456L, 876L, 78L, 687L, 378L, 378L, 34L, 53L, 43L), V2 = c(2L, 2L, 5L, 4L, 366L, 65L, 43L, 456L, 876L, 78L, 687L, 378L, 378L, 34L, 53L, 41L), V3 = c(10L, 20L, 10L, 20L, 10L, 20L, 1L, 0L, 1L, 2010L, 20L, 10L, 10L, 10L, 10L, 10L), V4 = c(2L, 10L, 31L, 2L, 2L, 5L, 2L, 5L, 1L, 52L, 1L, 2L, 52L, 6L, 2L, 1L), V5 = c(4L, 10L, 31L, 2L, 2L, 5L, 2L, 5L, 1L, 52L, 1L, 2L, 52L, 6L, 2L, 3L)), .Names = c("V1", "V2", "V3", "V4", "V5"), class = "data.frame", row.names = c(NA, -16L)) </code></pre> <p>Many thanks</p>
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