Defined in tensorflow/python/estimator/api/estimator/__init__.py.
Estimator: High level tools for working with models.
Modules
export module: Utility methods for exporting Estimator.
inputs module: Utility methods to create simple input_fns.
Classes
class BaselineClassifier: A classifier that can establish a simple baseline.
class BaselineRegressor: A regressor that can establish a simple baseline.
class BestExporter: This class exports the serving graph and checkpoints of the best models.
class BoostedTreesClassifier: A Classifier for Tensorflow Boosted Trees models.
class BoostedTreesRegressor: A Regressor for Tensorflow Boosted Trees models.
class DNNClassifier: A classifier for TensorFlow DNN models.
class DNNLinearCombinedClassifier: An estimator for TensorFlow Linear and DNN joined classification models.
class DNNLinearCombinedRegressor: An estimator for TensorFlow Linear and DNN joined models for regression.
class DNNRegressor: A regressor for TensorFlow DNN models.
class Estimator: Estimator class to train and evaluate TensorFlow models.
class EstimatorSpec: Ops and objects returned from a model_fn and passed to an Estimator.
class EvalSpec: Configuration for the "eval" part for the train_and_evaluate call.
class Exporter: A class representing a type of model export.
class FinalExporter: This class exports the serving graph and checkpoints in the end.
class LatestExporter: This class regularly exports the serving graph and checkpoints.
class LinearClassifier: Linear classifier model.
class LinearRegressor: An estimator for TensorFlow Linear regression problems.
class ModeKeys: Standard names for model modes.
class RunConfig: This class specifies the configurations for an Estimator run.
class TrainSpec: Configuration for the "train" part for the train_and_evaluate call.
class VocabInfo: Vocabulary information for warm-starting.
class WarmStartSettings: Settings for warm-starting in tf.estimator.Estimators.
Functions
classifier_parse_example_spec(...): Generates parsing spec for tf.parse_example to be used with classifiers.
regressor_parse_example_spec(...): Generates parsing spec for tf.parse_example to be used with regressors.
train_and_evaluate(...): Train and evaluate the estimator.