title: Scikit Naive Bayes Classification for text
body: <p>i am trying to use scikit for the Naive Basyes classification. i have couple of question (Also i am new to scikit)</p>
  
  <p>1) Scikit Algorithms want input as a numpy array and label as arrays. In case of text classification should i map each of my word with a number (id) , by maintaining a hash of words in vocab and a unique id associated with it? is this is standard practice in scikit?</p>
  
  <p>2) In case of assigning same text to more than one class how should i proceed. One obvious way is to replicate each training example one for each associated label. Any better representation exist?</p>
  
  <p>3) Similarly for the test data how will i get more than one class associated with a test?</p>
  
  <p>I am using <a href="http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html" rel="nofollow">http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html</a>
  as my base.</p>