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

tf.contrib.learn.TensorFlowRNNRegressor.restore(cls, path, config=None) Restores model from give path.

class tf.contrib.learn.BaseEstimator Abstract BaseEstimator class to train and evaluate TensorFlow models.

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

class tf.contrib.learn.LinearClassifier Linear classifier model. Train a linear model to classify

tf.contrib.learn.TensorFlowEstimator.__init__(model_fn, n_classes, batch_size=32, steps=200, optimizer='Adagrad', learning_rate=0.1, clip_gradients=5.0, class_weight=None

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

tf.contrib.learn.LinearClassifier.bias_

tf.contrib.learn.TensorFlowRNNRegressor.__repr__()

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