tf.contrib.learn.DNNRegressor.config

tf.contrib.learn.Estimator.__init__(model_fn=None, model_dir=None, config=None, params=None, feature_engineering_fn=None) Constructs

tf.contrib.learn.Estimator.get_variable_value(name) Returns value of the variable given by name. Args:

tf.contrib.learn.RunConfig.__init__(master=None, task=None, num_ps_replicas=None, num_cores=0, log_device_placement=False, gpu_memory_fraction=1, cluster_spec=None,

tf.contrib.learn.TensorFlowRNNRegressor.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None)

class tf.contrib.learn.ModeKeys Standard names for model modes. The following standard keys are

tf.contrib.learn.LinearClassifier.get_variable_value(name)

tf.contrib.learn.TensorFlowEstimator.__repr__()

tf.contrib.learn.DNNClassifier.predict(*args, **kwargs) Returns predicted classes for given features. (deprecated arguments)

tf.contrib.learn.BaseEstimator.fit(x=None, y=None, input_fn=None, steps=None, batch_size=None, monitors=None, max_steps=None) See