def update(self):
# Handle to storage for model parameters
params = self._parameters
# Make sure all my meta data is ready to go
params.validateMeta()
observation_vectors = []
truth_vectors = []
# Make sure my model data is ready to go
self._model_data.validate()
self._model_data.validateViews(self.getMetaData("db_views"))
# Check my model data
observation_vectors = self._model_data.getMetaData(
"observation_vectors")
truth_vectors = self._model_data.getMetaData("truth_vectors")
params.setMetaData("db_views", [])
# Houston we are go
mnb = MultinomialNB()
mnb.alpha = self.getMetaData("alpha")
mnb.fit_prior = self.getMetaData("fit_prior")
class_prior = self.getMetaData("class_prior")
if (class_prior != None):
mnb.class_prior = class_prior
mnb.fit(observation_vectors, truth_vectors)
params.setBinaryData("mnb_model", "application/pickle",
pickle.dumps(mnb))
self.finalize()
