tf.contrib.learn.train(graph, output_dir, train_op, loss_op, global_step_tensor=None, init_op=None, init_feed_dict=None, init_fn=None, log_every_steps=10, supervisor_is_chief=True

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

tf.contrib.learn.TensorFlowRNNRegressor.get_variable_names() Returns list of all variable names in this model.

tf.contrib.learn.LinearClassifier.model_dir

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

class tf.contrib.learn.LinearRegressor Linear regressor model. Train a linear regression model

tf.contrib.learn.DNNRegressor.weights_

tf.contrib.learn.Estimator.get_params(deep=True) Get parameters for this estimator. Args:

tf.contrib.learn.TensorFlowRNNClassifier.predict(x, axis=1, batch_size=None) Predict class or regression for x.

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