I am working on a project to classify snippets of text using the python nltk module and the naivebayes classifier.I am able to train on corpus data and classify another set of 开发者_开发技巧data but
When trying to load the punkt tokenizer... import nltk.data tokenizer = nltk.data.load(\'nltk:tokenizers/punkt/english.pickle\')
NLTK comes with some samples of corpus at: http://nltk.googlecode.com/svn/trunk/nltk_data/index.xml I want to have only text without encodings. I do not know how to extract such content. What I want
Am parsing some sentences (from the inaugural speech in the nltk corpus) with the format S -> NP VP, and I want to make sure I parsed them correctly, do these sentences 开发者_开发问答follow the afore
This question already has answers here: Creating a new corpus with NLTK (4 answers) Closed 9 years ago. Is there a way to create a corpus without having to have items in files. For instan
I am currently trying to build a general purpose (or as general as is practical) POS tagger with NLTK. I have dabbled with the brown and treebank corpora for training, but will probably be settling on
The task is to define a function count_vowels(text) that takes a string text, counts the vowels in text (using a Python dictionary for the counting), and returns the
say I have a tagged text (word, tag) in tuple format. i want to convert it to a string in order to make some changes to the tags. my function below only sees the last sentence in the text, i guess the
I reckoned that often the answer to my title is to go and read the documentations, but I ran through the NLTK book but it doesn\'t give the answer. I\'m kind of new to Python.
How to sum up the number of words frequency using fd.items() fr开发者_StackOverflow社区om FreqDist?
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