want to use feature selection technique
information gain, rank correlation etc..
If I understood your question, the process of FSelector should be fairly straightforward in R
install.packages("FSelector")
Also, I would recommend you to use Rattle Package to perform various ML routines without heavily depending on code. This package will also help you to use various feature selection methods.
Go to RStudio, install packages, install devtools using install.package("devtools"), then install FSelector using install.package("FSelector").
> chooseCRANmirror()
> utils:::menuInstallPkgs()
Warning in install.packages(lib = .libPaths()[1L], dependencies = NA, type = type) :
'lib = "C:/Program Files/R/R-4.0.2/library"' is not writable
also installing the dependencies ‘RWekajars’, ‘rJava’, ‘randomForest’, ‘RWeka’, ‘digest’, ‘entropy’
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/RWekajars_3.9.3-2.zip'
Content type 'application/zip' length 10032721 bytes (9.6 MB)
downloaded 9.6 MB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/rJava_0.9-13.zip'
Content type 'application/zip' length 1115499 bytes (1.1 MB)
downloaded 1.1 MB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/randomForest_4.6-14.zip'
Content type 'application/zip' length 250148 bytes (244 KB)
downloaded 244 KB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/RWeka_0.4-42.zip'
Content type 'application/zip' length 632654 bytes (617 KB)
downloaded 617 KB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/digest_0.6.25.zip'
Content type 'application/zip' length 245000 bytes (239 KB)
downloaded 239 KB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/entropy_1.2.1.zip'
Content type 'application/zip' length 80052 bytes (78 KB)
downloaded 78 KB
trying URL 'https://cran.case.edu/bin/windows/contrib/4.0/FSelector_0.31.zip'
Content type 'application/zip' length 94774 bytes (92 KB)
downloaded 92 KB
package ‘RWekajars’ successfully unpacked and MD5 sums checked
package ‘rJava’ successfully unpacked and MD5 sums checked
package ‘randomForest’ successfully unpacked and MD5 sums checked
package ‘RWeka’ successfully unpacked and MD5 sums checked
package ‘digest’ successfully unpacked and MD5 sums checked
package ‘entropy’ successfully unpacked and MD5 sums checked
package ‘FSelector’ successfully unpacked and MD5 sums checked
Firstly, Install.package("FSelector")
Then load the FSelector using Library("FSelector")
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