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

tf.contrib.learn.LinearClassifier.predict_proba(x=None, input_fn=None, batch_size=None, outputs=None, as_iterable=False) Runs

tf.contrib.learn.DNNClassifier.__init__(hidden_units, feature_columns, model_dir=None, n_classes=2, weight_column_name=None, optimizer=None, activation_fn=relu, dropout=None

tf.contrib.learn.TensorFlowEstimator.get_tensor(name) Returns tensor by name. Args:

tf.contrib.learn.RunConfig.is_chief

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

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

tf.contrib.learn.BaseEstimator.predict(*args, **kwargs) Returns predictions for given features. (deprecated arguments)

tf.contrib.learn.LinearClassifier.__init__(feature_columns, model_dir=None, n_classes=2, weight_column_name=None, optimizer=None, gradient_clip_norm=None, enable_centered_bias=None

tf.contrib.learn.TensorFlowRNNRegressor.get_variable_value(name) Returns value of the variable given by name.