similarity - How to find best resemblance between 1 row and the rest of dataframe in R? -

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how can find best resemblance between 1 particular row , rest of rows in dataframe?

i try explain mean. take @ dataframe:

df <- structure(list(person = 1:5, var1 = c(1l, 5l, 2l, 2l, 5l), var2 = c(4l,  4l, 3l, 2l, 2l), var3 = c(5l, 4l, 4l, 3l, 1l)), .names = c("person",  "var1", "var2", "var3"), class = "data.frame", row.names = c(na,  -5l))

how can find best resemblance between person 1 (row 1) , rest of rows (persons) in data frame. output should like: person 1 still in row 1 , rest of rows in order of best resemblance. simmilarity algorithm want use cosine or pearson. tried solve problem functions arules package, didn't match needs.

any ideas someone?

another idea define cosine function manually, , apply on data frame, i.e.

f1 <- function(x, y){   crossprod(x, y)/sqrt(crossprod(x) * crossprod(y)) }  df[c(1, order(sapply(2:nrow(df), function(i)                                  f1(unlist(df[1,-1]), unlist(df[i, -1]))),                                                            decreasing = true)+1),]

which gives,

   person var1 var2 var3 1      1    1    4    5 3      3    2    3    4 4      4    2    2    3 2      2    5    4    4 5      5    5    2    1




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