class DocToVector():
def __init__(self):
self.current_dir = os.path.dirname(__file__)
self.sorted_words = SortedWords()
self.get_dictionary()
self.preprocess = Preprocessor()
def get_dictionary(self):
pd_file = pd.read_csv(self.current_dir + '/../resources/word_frequency.csv')
self.sorted_words.set(pd_file['word'])
def add_to_dict_counter(self, docs):
docs = self.preprocess.split_space(docs)
def tf_idf(self, frequency_sentence, frequency_docs, num_words):
return (1 + math.log(frequency_sentence))*math.log(frequency_docs*1.0/num_words)
class DocToVector():
def __init__(self):
self.current_dir = os.path.dirname(__file__)
self.sorted_words = SortedWords()
self.get_dictionary()
self.preprocess = Preprocessor()
def get_dictionary(self):
pd_file = pd.read_csv(self.current_dir +
'/../resources/word_frequency.csv')
self.sorted_words.set(pd_file['word'])
def add_to_dict_counter(self, docs):
docs = self.preprocess.split_space(docs)
def tf_idf(self, frequency_sentence, frequency_docs, num_words):
return (1 + math.log(frequency_sentence)) * math.log(
frequency_docs * 1.0 / num_words)
