Nothing
simil()
for Fuzzy Jaccard similarity (#42).use_nan = FALSE
will suppress warnings in simil()
and dist()
.dist()
for Jensen-Shannon divergence as a symmetric version of Kullback-Leibler divergence.x
and y
are coerced to dgCMatrix for Matrix v1.4-2.dist()
for Jeffreys divergence. It is a symmetric version of Kullback-Leibler divergence (#31).rowSds()
, colSds()
, rowZeros()
and colZeros()
return row or column names. They also work with both dense and sparse matrices (#28).simil()
to correct misspelling (#26).simil()
and dist()
work with both dense and sparse matrices.use_nan = TRUE
can be used not only for correlation but for all the distance
and similarity measures.use_nan = TRUE
, in which case the computed correlation similarity
will be NaN
instead (#21).diag
argument to compute similarity/distance only for corresponding
rows or columns (#13).smooth
parameter to chisquared and kullback leibler distances to
solve negative values in sparse matrices (#15).stats::chisq.test()
(#14).drop0 = TRUE
(#17).drop0
argument to address the floating point precision issue (#10).dist()
(#11).rowSds()
, colSds()
, rowZeros()
and colZeros()
(#9).x != y
(#4).digits
argument to correct rounding errors in C++ (#5).Any scripts or data that you put into this service are public.
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