Nothing
Code
vectorize(enron, tokens = "character", remove_punct = F, remove_symbols = T,
remove_numbers = T, lowercase = T, n = 5, weighting = "rel", trim = T,
threshold = 1500)
Output
Document-feature matrix of: 218 documents, 1,500 features (54.35% sparse) and 3 docvars.
features
docs n n n n n n n w
known [Kevin.hyatt - Mail_1].txt 0.0015866720 0.005950020 0.0007933360
known [Kevin.hyatt - Mail_3].txt 0.0031298905 0.018257694 0.0015649452
known [Kevin.hyatt - Mail_4].txt 0.0008896797 0.004893238 0.0008896797
known [Kevin.hyatt - Mail_5].txt 0.0021929825 0.010087719 0.0017543860
unknown [Kevin.hyatt - Mail_2].txt 0.0026258206 0.014879650 0
unknown [Kimberly.watson - Mail_3].txt 0.0009976721 0.006983705 0.0003325574
features
docs n wa want s to
known [Kevin.hyatt - Mail_1].txt 0.0003966680 0.0023800079 0.0011900040
known [Kevin.hyatt - Mail_3].txt 0.0010432968 0 0.0010432968
known [Kevin.hyatt - Mail_4].txt 0.0004448399 0.0008896797 0
known [Kevin.hyatt - Mail_5].txt 0.0004385965 0 0
unknown [Kevin.hyatt - Mail_2].txt 0.0008752735 0.0004376368 0
unknown [Kimberly.watson - Mail_3].txt 0 0.0006651147 0.0003325574
features
docs to b to be o be
known [Kevin.hyatt - Mail_1].txt 0.0007933360 0.0007933360 0.0007933360
known [Kevin.hyatt - Mail_3].txt 0.0005216484 0.0005216484 0.0005216484
known [Kevin.hyatt - Mail_4].txt 0.0008896797 0.0008896797 0.0004448399
known [Kevin.hyatt - Mail_5].txt 0.0008771930 0.0008771930 0.0008771930
unknown [Kevin.hyatt - Mail_2].txt 0.0004376368 0.0004376368 0.0004376368
unknown [Kimberly.watson - Mail_3].txt 0.0003325574 0.0006651147 0.0003325574
features
docs e n w
known [Kevin.hyatt - Mail_1].txt 0.0007933360
known [Kevin.hyatt - Mail_3].txt 0.0020865936
known [Kevin.hyatt - Mail_4].txt 0.0008896797
known [Kevin.hyatt - Mail_5].txt 0.0013157895
unknown [Kevin.hyatt - Mail_2].txt 0.0017505470
unknown [Kimberly.watson - Mail_3].txt 0.0003325574
[ reached max_ndoc ... 212 more documents, reached max_nfeat ... 1,490 more features ]
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