DATA607_Project_4
RJM
2019-11-19
Calling the appropriate libraries:
library(tm); library(e1071); library(dplyr); library(wordcloud); ## Loading required package: NLP##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, union## Loading required package: RColorBrewerlibrary(caret); library(readtext); library(TAR); library(R.utils); ## Loading required package: lattice## Loading required package: ggplot2##
## Attaching package: 'ggplot2'## The following object is masked from 'package:NLP':
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## annotate## Loading required package: mvtnorm## Loading required package: R.oo## Loading required package: R.methodsS3## R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.## R.oo v1.23.0 successfully loaded. See ?R.oo for help.##
## Attaching package: 'R.oo'## The following object is masked from 'package:R.methodsS3':
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## throw## The following objects are masked from 'package:methods':
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## getClasses, getMethods## The following objects are masked from 'package:base':
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## attach, detach, load, save## R.utils v2.9.0 successfully loaded. See ?R.utils for help.##
## Attaching package: 'R.utils'## The following object is masked from 'package:utils':
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## timestamp## The following objects are masked from 'package:base':
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## cat, commandArgs, getOption, inherits, isOpen, nullfile,
## parse, warningslibrary(SnowballC)Assigning the right folders and files:
# Code to get the email message
spam_file <- "/Users/rmirza/Downloads/20021010_spam.tar.bz2"
ham_file <- "/Users/rmirza/Downloads/20021010_easy_ham.tar.bz2"
spam_file_unzip <- "/Users/rmirza/Downloads/20021010_spam.tar"
ham_file_unzip <- "/Users/rmirza/Downloads/20021010_easy_ham.tar"
bunzip2(spam_file, remove = FALSE, skip = TRUE)## [1] "/Users/rmirza/Downloads/20021010_spam.tar"
## attr(,"temporary")
## [1] FALSEbunzip2(ham_file, remove = FALSE, skip = TRUE)## [1] "/Users/rmirza/Downloads/20021010_easy_ham.tar"
## attr(,"temporary")
## [1] FALSE# Creating a combined directory to store the data
spam_ham_dir <- "/Users/rmirza/Documents/DATA607/spam_ham"
untar(spam_file_unzip, exdir = spam_ham_dir)
untar(ham_file_unzip, exdir = spam_ham_dir)
# Segregating the data in separate folders for spam and ham
spam_dir <- "/Users/rmirza/Documents/DATA607/spam_ham/spam"
ham_dir <- "/Users/rmirza/Documents/DATA607/spam_ham/easy_ham"
spam_files <- list.files(spam_dir)
ham_files <- list.files(ham_dir)Preparation of dataframes:
# Preparing data to create dataframes
spam_email_content <- NA
for(i in 1:length(spam_files))
{
file_address_spam <- paste0(spam_dir, "/", spam_files[1])
spam_lines <- readLines(file_address_spam)
list_spam <- list(paste(spam_lines, collapse="\n "))
spam_email_content = c(spam_email_content, list_spam)
}
# Code for the Spam Dataframe
spam_df <- data.frame()
spam_df <- as.data.frame(unlist(spam_email_content), stringsAsFactors = FALSE)
spam_df$type <- "Spam"
colnames(spam_df) <- c("email","type")
ham_email_content <- NA
for(i in 1:length(ham_files))
{
file_address_ham <- paste0(ham_dir, "/", ham_files[1])
ham_lines <- readLines(file_address_ham)
list_ham <- list(paste(ham_lines, collapse="\n"))
ham_email_content <- c(ham_email_content, list_ham)
}
# Code for the Ham Dataframe
ham_df <- data.frame()
ham_df <- as.data.frame(unlist(ham_email_content), stringsAsFactors = FALSE)
ham_df$type <- "Ham"
colnames(ham_df) <- c("email","type")
nrow(spam_df)## [1] 502nrow(ham_df)## [1] 2552combined_df <- rbind(spam_df, ham_df)
nrow(combined_df)## [1] 3054Cleaning the corpus:
original_corpus<- Corpus(VectorSource(combined_df$email))
# To cleand the corpus and create a word cloud to assess
# the type of words used in each type of messages
cleaned_corpus <- suppressWarnings(original_corpus %>%
# to convert into lower case
tm_map(content_transformer(tolower)) %>%
# to remove any punctuation
tm_map(removePunctuation) %>%
# to remove numbers
tm_map(removeNumbers) %>%
# to remove the stop words
tm_map(removeWords, stopwords()) %>%
# to stem the words into root word
tm_map(stemDocument) %>%
# to remove the white space
tm_map(stripWhitespace))# Checking the contents after cleaning
inspect(cleaned_corpus[1:3])## <<SimpleCorpus>>
## Metadata: corpus specific: 1, document level (indexed): 0
## Content: documents: 3
##
## [1] NA
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fccfdecdbfec mv cdbfdccfabaccaf mv dffaedefcefcf mv badfcaecbbdff mv bcedbefecbbb mv defeffeabba mv baaeaadaaf mv afeeeeeea mv bdffffafbcbf mv edbfddcdfcaf mv aceecdcdbbaccd mv bebdabaa mv baadafe mv afbfccdcbefdbd mv fcbcfdaefbdddd mv cdebafcfec mv ddbedeebdfd mv bfffcdcffeccfbbfc mv cfdfdbadaf mv aedfaadccf mv cfeadbeabbbaa mv aceeaffaeaf mv cccfbadcdfea mv dccfeacfbc mv bccbeefcb mv badbadbfcdbb mv edbbaabedd mv cdabddacefcaaf mv bdeebbcdcba mv beeacceaffbeea mv fcdebebeacdb mv ffebebaebbd mv abffebdfffaa mv eaeceefebbdef mv fcfbebfaececf mv efbfdfb mv cfddaddffedfb mv fffdeaccadea mv ddbbcecba mv dcadcecdacd mv fcfdedaceaea mv bdfdbfdadf mv ddeeacaedc mv adbacaaebfdac mv cdbdacdbebbeffd mv ef mv abfddbf mv bdcfcffebcb mv dfdaeebcfbfcea mv cdebaaecedbadcad mv babcfccfceeaaea mv fcdeadcafbbddffd mv ffcbead mv fdfddcbcbf mv cecebfbbcb mv afdaefadcd mv abcecabfbc mv efaccdbcdfadea mv bdfbffbffebebd mv dfeffedcad mv afbdfeebddeddd mv fbbdeeffccdddcba mv beeaafea mv ebdbbcdadf mv fdadbfead mv facdfbdcdaadcb mv bceadeafbcdea mv acafdaaa mv bbbecffffd mv fddeaceabec mv fdaebdddeeefcdfd mv abbcdbdaaac mv aecefabcedccd mv afcbbebdcbfac mv ffabddcba mv cebbaecaaeefaa mv fdfffdfed mv becaedfdbccbdebf mv dbdbeaedc mv dedcfaaebfddac mv ccdcfbdbff mv cefeef mv dfdebebcb mv abcfdeeaffeeba mv cdfbeacfb mv ebfeae mv cbdcdceadaf mv fadebbcbbcbeec mv dcfafbebfbaecfaa mv afaacfbacdbb mv fdbccffcdaeba mv febaaffdf mv acfbdedfbe mv ffbcfcbdbaecb mv afbafecbcfa mv beabfbceccacd mv afcaffaade mv bebfcdcaf mv cdcceeadca mv acddbffcfdcbbdcc mv dfacdebdcfabaeecfa mv ebaabaeaffcbbdf mv babeaadadbc mv cbdaccbdcbccd mv fdcfbcfddfd mv cbbeacceecc mv cefbfbdbcaaacda mv aedeedbef mv ecdabcfbfb mv bfcbcaad mv bbaaedaffdd mv baeacdcecbcdfcb mv edbdceffaf mv bcbefaeafbffa mv dcebabcdfab mv dccbcecd mv cffdbaadcdefc mv cmds bbcfcfdbcdefeebfinspect(cleaned_corpus[503:505])## <<SimpleCorpus>>
## Metadata: corpus specific: 1, document level (indexed): 0
## Content: documents: 3
##
## [1] NA
## [2] exmhworkersadminredhatcom thu aug returnpath exmhworkersadminexamplecom deliveredto zzzzlocalhostnetnoteinccom receiv localhost localhost phoboslabsnetnoteinccom postfix esmtp id dec zzzzlocalhost thu aug edt receiv phobo localhost imap fetchmail zzzzlocalhost singledrop thu aug ist receiv listmanexamplecom listmanexamplecom dogmaslashnullorg esmtp id gmbyrz zzzzexmhexamplecom thu aug receiv listmanexamplecom localhostlocaldomain listmanredhatcom postfix esmtp id thu aug edt deliveredto exmhworkerslistmanexamplecom receiv intmxcorpexamplecom intmxcorpexamplecom listmanredhatcom postfix esmtp id cfd exmhworkerslistmanredhatcom thu aug edt receiv maillocalhost intmxcorpexamplecom id gmbyg exmhworkerslistmanredhatcom thu aug receiv mxexamplecom mxexamplecom intmxcorpredhatcom smtp id gmbyy exmhworkersredhatcom thu aug receiv ratreepsuacth mxexamplecom smtp id gmbihl exmhworkersredhatcom thu aug receiv deltacsmuozau deltacoepsuacth ratreepsuacth esmtp id gmbwel thu aug ict receiv munnariozau localhost deltacsmuozau esmtp id gmbqpw thu aug ict robert elz kremunnariozau chris garrigu cwgdatedfaddeepeddycom cc exmhworkersexamplecom subject re new sequenc window inreplyto tmdadeepeddyvirciocom refer tmdadeepeddyvirciocom tmdadeepeddyvirciocom munnariozau tmdadeepeddyvirciocom tmdadeepeddyvirciocom mimevers contenttyp textplain charsetusascii messageid munnariozau xloop exmhworkersexamplecom sender exmhworkersadminexamplecom errorsto exmhworkersadminexamplecom xbeenther exmhworkersexamplecom xmailmanvers preced bulk listhelp mailtoexmhworkersrequestexamplecomsubjecthelp listpost mailtoexmhworkersexamplecom listsubscrib httpslistmanexamplecommailmanlistinfoexmhwork mailtoexmhworkersrequestredhatcomsubjectsubscrib listid discuss list exmh develop exmhworkersexamplecom listunsubscrib httpslistmanexamplecommailmanlistinfoexmhwork mailtoexmhworkersrequestredhatcomsubjectunsubscrib listarch httpslistmanexamplecommailmanprivateexmhwork date thu aug date wed aug chris garrigu cwgdatedfaddeepeddycom messageid tmdadeepeddyvirciocom cant reproduc error repeat like everi time without fail debug log pick happen pickit exec pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri exec pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri ftocpickmsg hit mark hit tkerror syntax error express int note run pick command hand delta pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri hit that hit come obvious version nmh im use delta pick version pick nmh compil fuchsiacsmuozau sun mar ict relev part mhprofil delta mhparam pick seq sel list sinc pick command work sequenc actual one that explicit command line search popup one come mhprofil get creat kre ps still use version code form day ago havent abl reach cvs repositori today local rout issu think exmhwork mail list exmhworkersredhatcom httpslistmanredhatcommailmanlistinfoexmhwork
## [3] exmhworkersadminredhatcom thu aug returnpath exmhworkersadminexamplecom deliveredto zzzzlocalhostnetnoteinccom receiv localhost localhost phoboslabsnetnoteinccom postfix esmtp id dec zzzzlocalhost thu aug edt receiv phobo localhost imap fetchmail zzzzlocalhost singledrop thu aug ist receiv listmanexamplecom listmanexamplecom dogmaslashnullorg esmtp id gmbyrz zzzzexmhexamplecom thu aug receiv listmanexamplecom localhostlocaldomain listmanredhatcom postfix esmtp id thu aug edt deliveredto exmhworkerslistmanexamplecom receiv intmxcorpexamplecom intmxcorpexamplecom listmanredhatcom postfix esmtp id cfd exmhworkerslistmanredhatcom thu aug edt receiv maillocalhost intmxcorpexamplecom id gmbyg exmhworkerslistmanredhatcom thu aug receiv mxexamplecom mxexamplecom intmxcorpredhatcom smtp id gmbyy exmhworkersredhatcom thu aug receiv ratreepsuacth mxexamplecom smtp id gmbihl exmhworkersredhatcom thu aug receiv deltacsmuozau deltacoepsuacth ratreepsuacth esmtp id gmbwel thu aug ict receiv munnariozau localhost deltacsmuozau esmtp id gmbqpw thu aug ict robert elz kremunnariozau chris garrigu cwgdatedfaddeepeddycom cc exmhworkersexamplecom subject re new sequenc window inreplyto tmdadeepeddyvirciocom refer tmdadeepeddyvirciocom tmdadeepeddyvirciocom munnariozau tmdadeepeddyvirciocom tmdadeepeddyvirciocom mimevers contenttyp textplain charsetusascii messageid munnariozau xloop exmhworkersexamplecom sender exmhworkersadminexamplecom errorsto exmhworkersadminexamplecom xbeenther exmhworkersexamplecom xmailmanvers preced bulk listhelp mailtoexmhworkersrequestexamplecomsubjecthelp listpost mailtoexmhworkersexamplecom listsubscrib httpslistmanexamplecommailmanlistinfoexmhwork mailtoexmhworkersrequestredhatcomsubjectsubscrib listid discuss list exmh develop exmhworkersexamplecom listunsubscrib httpslistmanexamplecommailmanlistinfoexmhwork mailtoexmhworkersrequestredhatcomsubjectunsubscrib listarch httpslistmanexamplecommailmanprivateexmhwork date thu aug date wed aug chris garrigu cwgdatedfaddeepeddycom messageid tmdadeepeddyvirciocom cant reproduc error repeat like everi time without fail debug log pick happen pickit exec pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri exec pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri ftocpickmsg hit mark hit tkerror syntax error express int note run pick command hand delta pick inbox list lbrace lbrace subject ftp rbrace rbrace sequenc mercuri hit that hit come obvious version nmh im use delta pick version pick nmh compil fuchsiacsmuozau sun mar ict relev part mhprofil delta mhparam pick seq sel list sinc pick command work sequenc actual one that explicit command line search popup one come mhprofil get creat kre ps still use version code form day ago havent abl reach cvs repositori today local rout issu think exmhwork mail list exmhworkersredhatcom httpslistmanredhatcommailmanlistinfoexmhworkInspecting the dataframes created:
combined_df_dtm<- DocumentTermMatrix(cleaned_corpus)
inspect(combined_df_dtm[1:4, 503:505])## <<DocumentTermMatrix (documents: 4, terms: 3)>>
## Non-/sparse entries: 0/12
## Sparsity : 100%
## Maximal term length: 14
## Weighting : term frequency (tf)
## Sample :
## Terms
## Docs cant cfd charsetusascii
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0Creation of word clouds to get an idea of the content of cleaned dataframes:
# Creating a spam word cloud
spam_tags <- which(combined_df$type == "Spam")
suppressWarnings(wordcloud(cleaned_corpus[spam_tags], min.freq=100))
# Creating a ham word cloud
ham_tags <- which(combined_df$type == "Ham")
suppressWarnings(wordcloud(cleaned_corpus[ham_tags], min.freq=100))
Pepraring the data for the Naives Bayes test:
# Using 70% of data for the training set and
# 30% for the test set.
train_combined_df <- createDataPartition(combined_df$email, p=0.70, list=FALSE)
set.seed(123)
combined_df_train <- combined_df[train_combined_df,]
combined_df_test <- combined_df[-train_combined_df,]
cleaned_corpus_train<- cleaned_corpus[train_combined_df]
cleaned_corpus_test<- cleaned_corpus[-train_combined_df]
combined_df_dtm_train <- combined_df_dtm[train_combined_df,]
combined_df_dtm_test <- combined_df_dtm[-train_combined_df,]
train_cleaned_dtm <- DocumentTermMatrix(cleaned_corpus_train)
test_cleaned_dtm <- DocumentTermMatrix(cleaned_corpus_test)
spam <- subset(train_combined_df,cleaned_corpus_train$type == "Spam")
ham <- subset(train_combined_df,cleaned_corpus_train$type == "Ham")
cleaned_count <- function(x) {
y <- ifelse(x > 0, 1, 0)
y <- factor(y, levels=c(0,1), labels=c("No", "Yes"))
y
}Running the test:
train_cleaned_set <- apply(train_cleaned_dtm, 2, cleaned_count)
test_cleaned_set <- apply(test_cleaned_dtm, 2, cleaned_count)
data_classifier <- naiveBayes(train_cleaned_set, factor(combined_df_train$type))
Test_output <- predict(data_classifier, newdata = test_cleaned_set)
table(Test_output, combined_df_test$type)##
## Test_output Ham Spam
## Ham 765 0
## Spam 0 150Conclusion:
The results indicate that there are no “false positives” as result of the Naives Bayes test. However, I feel that my model has some issues (probably overfitting) that have caused the model to show each of the spam and ham properly fished out. The model shows that there are 765 hams and 150 spams as of it stands now with none of them erroneously designated.