def testIrisMomentum(self):
random.seed(42)
iris = datasets.load_iris()
x_train, x_test, y_train, y_test = train_test_split(iris.data,
iris.target,
test_size=0.2,
random_state=42)
def custom_optimizer():
return momentum_lib.MomentumOptimizer(learning_rate=0.01,
momentum=0.9)
classifier = learn.DNNClassifier(
hidden_units=[10, 20, 10],
feature_columns=learn.infer_real_valued_columns_from_input(
x_train),
n_classes=3,
optimizer=custom_optimizer,
config=learn.RunConfig(tf_random_seed=1))
classifier.fit(x_train, y_train, steps=400)
predictions = np.array(list(classifier.predict_classes(x_test)))
score = accuracy_score(y_test, predictions)
self.assertGreater(score, 0.65,
"Failed with score = {0}".format(score))
def test_pandas_series(self):
if HAS_PANDAS:
import pandas as pd # pylint: disable=g-import-not-at-top
random.seed(42)
iris = datasets.load_iris()
data = pd.DataFrame(iris.data)
labels = pd.Series(iris.target)
classifier = learn.LinearClassifier(
feature_columns=learn.infer_real_valued_columns_from_input(
data),
n_classes=3)
classifier.fit(data, labels, steps=100)
score = accuracy_score(labels,
list(classifier.predict_classes(data)))
self.assertGreater(score, 0.5,
"Failed with score = {0}".format(score))
def test_dask_iris_classification(self):
if HAS_DASK and HAS_PANDAS:
import pandas as pd # pylint: disable=g-import-not-at-top
import dask.dataframe as dd # pylint: disable=g-import-not-at-top
random.seed(42)
iris = datasets.load_iris()
data = pd.DataFrame(iris.data)
data = dd.from_pandas(data, npartitions=2)
labels = pd.DataFrame(iris.target)
labels = dd.from_pandas(labels, npartitions=2)
classifier = learn.LinearClassifier(
feature_columns=learn.infer_real_valued_columns_from_input(
data),
n_classes=3)
classifier.fit(data, labels, steps=100)
predictions = data.map_partitions(classifier.predict).compute()
score = accuracy_score(labels.compute(), predictions)
self.assertGreater(score, 0.5,
"Failed with score = {0}".format(score))
def testIris(self):
iris = datasets.load_iris()
self.assertTupleEqual(iris.data.shape, (150, 4))
self.assertTupleEqual(iris.target.shape, (150, ))