def test_default(self): config = Config.default() self.assertEqual('AROW', config['method'])
'Species': Schema.LABEL, 'Sepal.Length': Schema.NUMBER, 'Sepal.Width': Schema.NUMBER, 'Petal.Length': Schema.NUMBER, 'Petal.Width': Schema.NUMBER, }) # Create a Dataset, which is an abstract representation of a set of data # that can be fed to Services like Classifier. `shuffle()` returns a new # Dataset whose order of data is shuffled. Note that datasets are immutable # objects. dataset = Dataset(loader, schema).shuffle() # Create a Classifier Service. # Classifier process starts using a default configuration. cfg = Config.default() classifier = Classifier.run(cfg) # You can also connect to an existing service instead. #classifier = Classifier('127.0.0.1', 9199) # Train the classifier with every data in the dataset. for (idx, label) in classifier.train(dataset): # You can peek the datum being trained. print("Train: {0}".format(dataset[idx])) # Save the trained model file. print("Saving model file...") classifier.save('example_snapshot') # Classify using the same dataset.
def test_default(self): config = Config.default() self.assertEqual('AROW', config['method'])