def train(self, num):
"""Trains a model with num samples.
Args:
num: int. The number of samples to run with.
Returns:
dict. The dict representing the resulting classifier model.
"""
string_classifier = StringClassifier()
string_classifier.load_examples(self.examples[:num])
classifier_dict = string_classifier.to_dict()
return classifier_dict
def train(self, num):
"""Trains a model with num samples.
Args:
num: int. The number of samples to run with.
Returns:
dict. The dict representing the resulting classifier model.
"""
string_classifier = StringClassifier()
string_classifier.load_examples(self.examples[:num])
classifier_dict = string_classifier.to_dict()
return classifier_dict
def predict(self, num):
"""Predicts the label for num samples with self.classifier.
Args:
num: int. The number of samples to predict the label for.
"""
if not self.classifier_model_dict:
raise Exception('No classifier found')
string_classifier = StringClassifier()
string_classifier.from_dict(self.classifier_model_dict)
doc_ids = string_classifier.add_docs_for_predicting(
self.docs_to_classify[:num])
for doc_id in doc_ids:
string_classifier.predict_label_for_doc(doc_id)
def predict(self, num):
"""Predicts the label for num samples with self.classifier.
Args:
num: int. The number of samples to predict the label for.
"""
if not self.classifier_model_dict:
raise Exception('No classifier found')
string_classifier = StringClassifier()
string_classifier.from_dict(self.classifier_model_dict)
doc_ids = string_classifier.add_docs_for_predicting(
self.docs_to_classify[:num])
for doc_id in doc_ids:
string_classifier.predict_label_for_doc(doc_id)
