tf.contrib.learn.TensorFlowRNNRegressor.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.predict_proba(*args, **kwargs) Returns prediction probabilities for given features. (deprecated

tf.contrib.learn.TensorFlowRNNRegressor.set_params(**params) Set the parameters of this estimator. The

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

tf.contrib.learn.TensorFlowRNNRegressor.bias_ Returns bias of the rnn layer.

tf.contrib.learn.TensorFlowRNNClassifier.save(path) Saves checkpoints and graph to given path. Args:

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

tf.contrib.learn.BaseEstimator.partial_fit(x=None, y=None, input_fn=None, steps=1, batch_size=None, monitors=None) Incremental

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