How to deal with large data sets while applying linear regression in R?

@shashwat.2014 wrote:

Hi everyone,

I am working on a dataset with 25 variables and around 1000000 rows. When I applied linear regression :
lmao<-lm(Sales~.,data=combined)
It gave me the error :

     Error: cannot allocate vector of size 4.1 Gb
    In addition: Warning messages:
    1: In model.matrix.default(mt, mf, contrasts) :
      Reached total allocation of 4027Mb: see help(memory.size)
    2: In model.matrix.default(mt, mf, contrasts) :
      Reached total allocation of 4027Mb: see help(memory.size)
    3: In model.matrix.default(mt, mf, contrasts) :
      Reached total allocation of 4027Mb: see help(memory.size)
    4: In model.matrix.default(mt, mf, contrasts) :
      Reached total allocation of 4027Mb: see help(memory.size)

My configuration is 64 bit Windows 10 with a 4GB RAM. Please suggest how can I optimise the memory space used by the model.

Thanks in advance!

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