Mike Spaner mspan

## rf_phone_tutorial.R
library(randomForest)

# for reference, how to download cleaned up dataset we'll be using.

# url = "https://spark-public.s3.amazonaws.com/dataanalysis/samsungData.rda"
# destfile = "./samsungData2.rda"
# download.file(url, destfile, method="curl", quiet = FALSE, mode = "wb",cacheOK = TRUE)

load("~/Dropbox/random_phone_tutorial/samsungData.rda")

## RandomForestsInTen_final.ipynb

      
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                mspan
                / RandomForestsInTen_final.ipynb
            
            
              Created
              September 26, 2013 00:10
            
              
                Overview of Random Forests for newhaven.io presentation
              
          
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## find-duplicate-files.R
library("digest")
test_dir= "/Volumes/Public/book_k/photo_backup"
filelist <- dir(test_dir, pattern = "JPG|AVI", recursive=TRUE, all.files =TRUE, full.names=TRUE)

# a concise, vectorized solution
# http://stackoverflow.com/questions/14060423/how-to-vectorize-this-r-code-using-plyr-apply-or-similar
md5s<-sapply(filelist,digest,file=TRUE,algo="md5", length = 5000)
duplicate_files = split(filelist,md5s)

# now let's divide the list into duplicates ( length > 1) and uniques ( length - 1)
	library(randomForest)

	# for reference, how to download cleaned up dataset we'll be using.

	# url = "https://spark-public.s3.amazonaws.com/dataanalysis/samsungData.rda"
	# destfile = "./samsungData2.rda"
	# download.file(url, destfile, method="curl", quiet = FALSE, mode = "wb",cacheOK = TRUE)

	load("~/Dropbox/random_phone_tutorial/samsungData.rda")
	library("digest")
	test_dir= "/Volumes/Public/book_k/photo_backup"
	filelist <- dir(test_dir, pattern = "JPG\|AVI", recursive=TRUE, all.files =TRUE, full.names=TRUE)

	# a concise, vectorized solution
	# http://stackoverflow.com/questions/14060423/how-to-vectorize-this-r-code-using-plyr-apply-or-similar
	md5s<-sapply(filelist,digest,file=TRUE,algo="md5", length = 5000)
	duplicate_files = split(filelist,md5s)

	# now let's divide the list into duplicates ( length > 1) and uniques ( length - 1)