Please respond to the list; there are more people answering there.
As explained in the documentation gower_dist performes a pairwise
comparison of the two arguments recycling the shortest one if needed, so
indeed gower_dist(iris[1:5, ], iris) doesn't do what you want.
Possible solutions are:
tmp <- split(iris[1:150, ], seq_len(150))
sapply(gower_dist, iris)
and:
library(dplyr)
library(tidyr)
pairs <- expand.grid(x = 1:5, y = 1:nrow(iris))
pairs$dist <- gower_dist(iris[pairs$x, ], iris[pairs$y, ])
pairs %>% spread(y, dist)
Don't know which one is faster. And there are probably various other
solutions too.
--
Jan
On 27-10-18 18:04, Aerenbkts bkts wrote:
Dear Jan
Thanks for your help. Actually it works for the first element. But I
tried to calculate distance values for the first N rows. For example;
gower_dist(iris[1:5,], iris) // gower distance for the first 5 rows.
but it did not work. Do you have any suggestion about it?
On Fri, 26 Oct 2018 at 21:31, Jan van der Laan <rh...@eoos.dds.nl
<mailto:rh...@eoos.dds.nl>> wrote:
Using another implementation of the gower distance:
library(gower)
gower_dist(iris[1,], iris)
HTH,
Jan
On 26-10-18 15:07, Aerenbkts bkts wrote:
> I have a data-frame with 30k rows and 10 features. I would like to
> calculate distance matrix like below;
>
> gower_dist <- daisy(data-frame, metric = "gower"),
>
>
> This function returns whole dissimilarity matrix. I want to get just
> the first row.
> (Just distances of the first element in data-frame). How can I
do it?
> Do you have an idea?
>
>
> Regards
>
> [[alternative HTML version deleted]]
>
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