I would like to do a classification but I have this error :
cah_souscrip_4comp<-HCPC(acp_souscrip_4comp)
Error: cannot allocate vector of size 65.2 Gb
The size of my file is :
object.size(acp_souscrip_4comp)
65628440 bytes
So almost 66Mb. How this could need to allocate a vector bigger than 65.2 Gb ?
I'm using 64-bit version of RStudio. I've tried to use various packages such as bigmemory (even it's not that big), to change the limit using memory.limit() :
memory.limit()
[1] 1e+10
Always same error. I don't find any solution on forums, except the ones I've tried but didn't work for me.
Numbers of rows : 132 265 obs. I would like to keep all of them if possible, I don't feel like this is huge.
It worked for 1 000, I'm trying for 20 000 and I have performance issue.
I haven't done statistics for a while, but I'm sad having 130 000 obs and using maybe less than 10 000. I don't feel like 130 000 obs is a huge of data. Can't R handle it ? I would agree for 100 000, that won't change the results I guess.
Or may I do something wrong ? I followed some tutoriels for the implementation, but of course with example data there is no performance issue.
I will look at prcomp method, hclust I had the same pb but I will try with prcomp first.
The method I wanted to apply is to classify the population depending of the main variables. I studied this method a long time ago and I've seen this recently on books or online, but they never talk about the limit of size. I didn't think that 100 000 rows for around 10 var would be too much data.
I'm gonna try a bootstrapping approach also.
Oh I didn't answer for the package of HCPC : it's FactoMineR.