# Copyright 2016 The TensorFlow Authors. All Rights Reserved.

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# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

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# http://www.apache.org/licenses/LICENSE-2.0

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# Unless required by applicable law or agreed to in writing, software

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"""Example of DNNClassifier for Iris plant dataset."""

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

from sklearn import cross_validation

from sklearn import metrics

import tensorflow as tf

from tensorflow.contrib import learn

def main(unused_argv):

# Load dataset.

iris = learn.datasets.load_dataset('iris')

x_train, x_test, y_train, y_test = cross_validation.train_test_split(

iris.data, iris.target, test_size=0.2, random_state=42)

# Build 3 layer DNN with 10, 20, 10 units respectively.

feature_columns = learn.infer_real_valued_columns_from_input(x_train)

classifier = learn.DNNClassifier(

feature_columns=feature_columns, hidden_units=[10, 20, 10], n_classes=3)

# Fit and predict.

classifier.fit(x_train, y_train, steps=200)

score = metrics.accuracy_score(y_test, classifier.predict(x_test))

print('Accuracy: {0:f}'.format(score))

if __name__ == '__main__':

tf.app.run()