python
import skflow
from sklearn import datasets, metrics, preprocessing
iris = datasets.load_iris()
X = iris.data
y = iris.target
X = preprocessing.StandardScaler().fit_transform(X)
X_train, X_test, y_train, y_test = skflow.train_test_split(X, y, test_size=0.2)
classifier = skflow.TensorFlowDNNClassifier(hidden_units=[10, 20, 10], n_classes=3, steps=200)
classifier.fit(X_train, y_train)
y_pred = classifier.predict(X_test)
accuracy = metrics.accuracy_score(y_test, y_pred)
