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[英]R - How to apply terms from training document-term-matrix (dtm) to test dtm (both unigrams and bigrams)?
[英]Keep only certain bigrams in document term matrix R
问题:如何仅在文档术语矩阵或我要保留的双字母(术语)列表中使双字母“不好”?
我想将其应用于非常大的文档术语矩阵。 我尝试将术语矩阵转换为矩阵,但矢量大小超过1000 Gb。
码:
dd <- data.frame(
id = 10:13,
text = c("No wonderful, then, that ever",
"So that in many cases such a ",
"But there were still other and",
"Not even at the rationale"), stringsAsFactors = F)
library(tm)
library(RWeka)
myReader <- readTabular(mapping = list(content = "text", id = "id"))
#create v corpus
tm <- VCorpus(DataframeSource(dd), readerControl = list(reader = myReader))
#n-gram tokenizer
Tokenizer <- function(x) NGramTokenizer(x, Weka_control(min = 2, max = 2))
#create document term matrix using Tokenizer
dtm <- TermDocumentMatrix(tm, control = list(tokenize = Tokenizer))
inspect(dtm)
输出:
Docs
Terms 10 11 12 13
at the 0 0 0 1
but there 0 0 1 0
cases such 0 1 0 0
even at 0 0 0 1
in many 0 1 0 0
many cases 0 1 0 0
no wonderful 1 0 0 0
not even 0 0 0 1
other and 0 0 1 0
so that 0 1 0 0
still other 0 0 1 0
such a 0 1 0 0
that ever 1 0 0 0
that in 0 1 0 0
the rationale 0 0 0 1
then that 1 0 0 0
there were 0 0 1 0
were still 0 0 1 0
wonderful then 1 0 0 0
当时以为它是DTM,所以更加复杂。
问题解决了:
d_sel <- dtm[c('no wonderful', 'there were'),]
inspect(d_sel)
Docs
Terms 10 11 12 13
no wonderful 1 0 0 0
there were 0 0 1 0
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