def processConversation(conversation):
global bag_of_words
bag_of_words = {}
sentences = conversation.split(".")
tokenized = PreProcess.tokenize_sentences(sentences)
filtered = PreProcess.RemovePunctAndStopWords(tokenized)
bag_of_words = FreqDist(word.lower() for word in filtered)
def processConversation(conversation, category):
global bag_of_words, documentClass
bag_of_words = {}
sentences = conversation.split(".")
tokenized = PreProcess.tokenize_sentences(sentences)
filtered = PreProcess.RemovePunctAndStopWords(tokenized)
for word in filtered:
if word in bag_of_words:
bag_of_words[word] = int(bag_of_words[word]) + 1
else:
bag_of_words[word] = 1
#total=len(filtered)
#bag_of_words=calculateFrequencies(total)
addTermFrequency(bag_of_words)
def processConversation(conversation,category):
global bag_of_words,documentClass
bag_of_words={}
sentences=conversation.split(".")
tokenized=PreProcess.tokenize_sentences(sentences)
filtered=PreProcess.RemovePunctAndStopWords(tokenized)
for word in filtered:
if word in bag_of_words:
bag_of_words[word]=int(bag_of_words[word])+1
else:
bag_of_words[word]=1
total=len(filtered)
bag_of_words=calculateFrequencies(total)
if category in documentClass:
new_dict=merge_two_dicts(documentClass[category],bag_of_words)
documentClass[category]=new_dict
else:
documentClass[category]=bag_of_words
