return SentimentClassifier(corpus_set)
def __init__(self, corpus_set):
self._trained = False
self._corpus_set = corpus_set
self._c = 2 ** 7
self._model = None
@property
def c(self):
return self._c
@c.setter
def c(self, cc):
self._c = cc
def reset_model(self):
self._model = None
def words(self):
return self._corpus_set.words
def classify(self, string):
if self._model is None:
self._model = self.fit_model()
prediction = self._model.predict(self._corpus_set.feature_vector(string))
return self.present_answer(prediction)
def fit_model(self):
self._corpus_set.calculate_sparse_vectors()
y_vec = self._corpus_set.yes
x_mat = self._corpus_set.xes ...