My code below works fine unless I use create a DocumentTermMatrix with more that 3000 terms. This line:
movie_dict <- findFreqTerms(movie_dtm_train, 8)
movie_dtm_hiFq_train <- DocumentTermMatrix(movie_corpus_train, list(dictionary = movie_dict))
Fails with:
Error in simple_triplet_matrix(i = i, j = j, v = as.numeric(v), nrow = length(allTerms), :
'i, j, v' different lengths
In addition: Warning messages:
1: In mclapply(unname(content(x)), termFreq, control) :
all scheduled cores encountered errors in user code
2: In simple_triplet_matrix(i = i, j = j, v = as.numeric(v), nrow = length(allTerms), :
NAs introduced by coercion
Is there some way I can handle this? Is a 3000*60000 matrix just too big for DocumentTermMatrix? This seems pretty small for document classification though..
Full code snippet:
n1 <- 60000
n2 <- 70000
#******* loading the data ******************************************
#kaggle sentiment_analysis dataset
movie_all <- read.delim('train.tsv', stringsAsFactors=FALSE)
movie_raw <- movie_all[1:(n2),]
#******* cleaning the corpus ***************************************
movie_corpus <- Corpus(VectorSource(movie_raw$Phrase))
movie_corpus_clean <- tm_map(movie_corpus, content_transformer(tolower))
movie_corpus_clean <- tm_map(movie_corpus_clean, removeNumbers)
movie_corpus_clean <- tm_map(movie_corpus_clean, removeWords, stopwords())
movie_corpus_clean <- tm_map(movie_corpus_clean, removePunctuation)
movie_corpus_clean <- tm_map(movie_corpus_clean, stripWhitespace)
movie_dtm <- DocumentTermMatrix(movie_corpus_clean)
#*********** break out data into train/test sets *******************
movie_train <- movie_raw[1:(n1),]
movie_corpus_train <- movie_corpus_clean[1:(n1)]
movie_dtm_train <- movie_dtm[1:(n1),]
#*********** remove rare words from document term matrix ***********
movie_dict <- findFreqTerms(movie_dtm_train, 8)
movie_dtm_hiFq_train <- DocumentTermMatrix(movie_corpus_train, list(dictionary = movie_dict))
Edit This fails:
movie_dtm_hiFq_train <- DocumentTermMatrix(movie_corpus_train[1:60000], list(dictionary = movie_dict))
but this works:
d1 <- DocumentTermMatrix(movie_corpus_train[1:30000], list(dictionary = movie_dict))
d2 <- DocumentTermMatrix(movie_corpus_train[30000:60000], list(dictionary = movie_dict))
movie_dtm_hiFq_train <- c(d1, d2)
which leads me to believe this must be a size issue..