January 2016
Intermediate to advanced
337 pages
11h 50m
English
Content preview from Text Mining and Visualization
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214 Text Mining and Visualization: Case Studies Using Open-Source Tools
pos_feat = prepare_review(pos_ids)
neg_feat = prepare_review(neg_ids,
reviewtype=’neg’)
Listing 11: Calling the prepare review function with default parameter values
pos_feat = prepare_review(pos_ids,
removepunctuation=1,
minwordsize=4,
removestopwords=1,
stemwords=1,
ngramsize=2)
neg_feat = prepare_review(neg_ids,
removepunctuation=1,
minwordsize=4,
removestopwords=1,
stemwords=1,
ngramsize=2,
reviewtype=’neg’)
Listing 12: An extreme example of calling the prepare review function
>>> bunch.keys()
dict_keys([’target’, ’target_names’, ’filenames’, ’DESCR’, ’data’])
>>> bunch.target[0]
0
>>> bunch.target_names[0] ...
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