tf.contrib.learn.DNNRegressor.weights_

tf.contrib.learn.DNNRegressor.__init__(hidden_units, feature_columns, model_dir=None, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None, gra

tf.contrib.learn.TensorFlowRNNClassifier.fit(x, y, steps=None, monitors=None, logdir=None) Neural network model from provided

tf.contrib.learn.LinearClassifier.model_dir

tf.contrib.learn.BaseEstimator.__init__(model_dir=None, config=None) Initializes a BaseEstimator instance.

tf.contrib.learn.read_batch_examples(file_pattern, batch_size, reader, randomize_input=True, num_epochs=None, queue_capacity=10000, num_threads=1, read_batch_size=1

tf.contrib.learn.Estimator.export(*args, **kwargs) Exports inference graph into given dir. (deprecated arguments)

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

tf.contrib.learn.LinearRegressor.dnn_bias_ Returns bias of deep neural network part.

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