In [3]:

    

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

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from sklearn import model_selection
from sklearn import metrics
import tensorflow as tf


    

In [4]:

    

# load data
iris = tf.contrib.learn.datasets.load_dataset('iris')
x_train, x_test, y_train, y_test = model_selection.train_test_split(
    iris.data, iris.target, test_size=0.2, random_state=42)

# build 3 layers DNN with 10, 20, 10 units respectively.
feature_columns = tf.contrib.learn.infer_real_valued_columns_from_input(x_train)
classifier = tf.contrib.learn.DNNClassifier(feature_columns=feature_columns, hidden_units=[20,30,10,10], n_classes=3)

# Fit and predict
classifier.fit(x_train, y_train, steps=200)
predictions = list(classifier.predict(x_test, as_iterable=True))
score = metrics.accuracy_score(y_test, predictions)

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


    

    




WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmp_twiyk_2
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_save_summary_steps': 100, '_tf_config': gpu_options {
  per_process_gpu_memory_fraction: 1.0
}
, '_is_chief': True, '_tf_random_seed': None, '_evaluation_master': '', '_save_checkpoints_steps': None, '_environment': 'local', '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f661019ba20>, '_task_type': None, '_keep_checkpoint_every_n_hours': 10000, '_master': '', '_save_checkpoints_secs': 600, '_task_id': 0, '_keep_checkpoint_max': 5, '_num_ps_replicas': 0}
WARNING:tensorflow:From <ipython-input-4-1c32491e6a58>:11: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From <ipython-input-4-1c32491e6a58>:11: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.






    




/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py:247: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
  equality = a == b






    




INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Saving checkpoints for 1 into /tmp/tmp_twiyk_2/model.ckpt.
INFO:tensorflow:loss = 1.36598, step = 1
INFO:tensorflow:global_step/sec: 357.577
INFO:tensorflow:loss = 0.112293, step = 101
INFO:tensorflow:Saving checkpoints for 200 into /tmp/tmp_twiyk_2/model.ckpt.
INFO:tensorflow:Loss for final step: 0.0816449.
WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py:374: calling BaseEstimator.predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
Accurary: 1.000000

In [ ]: