title: What is this feature column and how does it affect the training?
body: <p>I'm relatively new to Tensor Flow. What is this feature column and how does it affect the training? </p>
  
  <p>When I implement a code like below, this numeric column is created as a feature column. I would like to understand the use.</p>
  
  <pre><code>feature_columns = [tf.feature_column.numeric_column("x", shape=[1])]
  
  estimator = tf.estimator.LinearRegressor(feature_columns=feature_columns)
  
  x_train = np.array([1., 2., 3., 4.])
  y_train = np.array([0., -1., -2., -3.])
  x_eval = np.array([2., 5., 8., 1.])
  y_eval = np.array([-1.01, -4.1, -7, 0.])
  
  input_fn = tf.estimator.inputs.numpy_input_fn(
      {"x": x_train}, y_train, batch_size=4, num_epochs=None, shuffle=True)
  train_input_fn = tf.estimator.inputs.numpy_input_fn(
  {"x": x_train}, y_train, batch_size=4, num_epochs=1000, shuffle=False)
  eval_input_fn = tf.estimator.inputs.numpy_input_fn(
  {"x": x_eval}, y_eval, batch_size=4, num_epochs=1000, shuffle=False)
  
  estimator.train(input_fn=input_fn, steps=10000)
  train_metrics = estimator.evaluate(input_fn=train_input_fn)
  eval_metrics = estimator.evaluate(input_fn=eval_input_fn)
  print("\n\ntrain metrics: %r"% train_metrics)
  print("eval metrics: %r"% eval_metrics)
  </code></pre>