Example #1
0
 def add_type_frequencies(self, sent):
     a = nltktest.tag_in_twos(sent)
     # [TAG, TAG2, TAG3]
     for elem in a:
         if elem[1] in self.type_frequencies:
             val_arr = self.type_frequencies[elem[1]]
             found = False
             for i in range(0, len(val_arr)):
                 if elem[0] == val_arr[i][0]:
                     found = True
                     val_arr[i] = (val_arr[i][0], val_arr[i][1] + 1)
             if not found:
                 self.type_frequencies[elem[1]].append((elem[0], 1))
         else:
             self.type_frequencies[elem[1]] = [(elem[0], 1)]
     print(self.type_frequencies)
Example #2
0
 def add_type_frequencies(self, sent):
     a = nltktest.tag_in_twos(sent)
     # [TAG, TAG2, TAG3]
     for elem in a:
         if elem[1] in self.type_frequencies:
             val_arr = self.type_frequencies[elem[1]]
             found = False
             for i in range(0, len(val_arr)):
                 if elem[0] == val_arr[i][0]:
                     found = True
                     val_arr[i] = (val_arr[i][0], val_arr[i][1]+1)
             if not found:
                 self.type_frequencies[elem[1]].append((elem[0], 1))
         else:
             self.type_frequencies[elem[1]] = [(elem[0], 1)]
     print(self.type_frequencies)
Example #3
0
 def train(self, sent):
     """
     Single sentence will be used to fill the state transition matrix.
     :param sent: the sentence to be trained on
     """
     a = nltktest.tag_in_twos(sent)
     prev_list = ()
     for i in range(0, len(a)):
         if prev_list in self.model.keys():
             val_arr = self.model[prev_list]
             found = False
             for j in range(0, len(val_arr)):
                 if a[i] == val_arr[j][0]:
                     found = True
                     val_arr[j] = (val_arr[j][0], val_arr[j][1] + 1)
             if not found:
                 self.model[prev_list].append((a[i], 1))
         else:
             self.model[prev_list] = [(a[i], 1)]
         prev_list = prev_list + tuple([a[i]])
         if (len(prev_list) > self.n):
             prev_list = prev_list[1:]
     self.model[prev_list] = ()
Example #4
0
 def train(self, sent):
     """
     Single sentence will be used to fill the state transition matrix.
     :param sent: the sentence to be trained on
     """
     a = nltktest.tag_in_twos(sent)
     prev_list = ()
     for i in range(0, len(a)):
         if prev_list in self.model.keys():
             val_arr = self.model[prev_list]
             found = False
             for j in range(0, len(val_arr)):
                 if a[i] == val_arr[j][0]:
                     found = True
                     val_arr[j] = (val_arr[j][0], val_arr[j][1]+1)
             if not found:
                 self.model[prev_list].append((a[i], 1))
         else:
             self.model[prev_list] = [(a[i], 1)]
         prev_list = prev_list + tuple([a[i]])
         if(len(prev_list) > self.n):
             prev_list = prev_list[1:]
     self.model[prev_list] = ()