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    Parallel Computing

    With a Mac, parallel computing can be achieved with package multicore. Unfortunately, it does not work under Windows.

    A simple way for parallel computing under Windows (and also Mac) is using package snowfall, which can work with multi-CPU or multi-core on a single machine, as well as a cluster of multiple machines.

    For parallel computing on a single machine, it is simple and easy as below.

    > library (snowfall)
    # initialize cluster
    > sfInit (parallel=TRUE , cpus=4)
    # parallel computing
    > result <- sfLapply(1:10, log)
    # stop cluster
    > sfStop ()

    Simply replace "1:10" and "log" with your parameter and function to make you own parallel computing.

    Function sfLapply() is a parallelized version of lapply(). Some other fuctions are sfSapply, sfApply, sfRapply and sfCapply.

    More examples on data mining with R can be found in my book "R and Data Mining: Examples and Case Studies", which is downloadable as a .PDF file at the link.