R ile Metin Analizine Giriş
Maham Faisal Khan
Senior Data Science Content Developer
sparse_review
Terms Docs admit ago albeit amazing angle awesome 4 1 0 1 0 0 0 5 0 1 0 1 1 0 3 0 0 0 0 0 1 2 0 0 0 0 0 0
tidy_review %>% count(word, id) %>% cast_dtm(id, word, n)
<<DocumentTermMatrix (documents: 1791, terms: 9669)>> Non-/sparse entries: 62766/17252622 Sparsity : 100% Maximal term length: NA Weighting : term frequency (tf)
dtm_review <- tidy_review %>% count(word, id) %>% cast_dtm(id, word, n) %>% as.matrix() dtm_review[1:4, 2000:2004]
dtm_review <- tidy_review %>% count(word, id) %>% cast_dtm(id, word, n) %>% as.matrix()
dtm_review[1:4, 2000:2004]
Terms Docs consecutive consensus consequences considerable considerably 223 0 0 0 0 0 615 0 0 0 0 0 1069 0 0 0 0 0 425 0 0 0 0 0
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