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'])