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A time series library in TensorFlow (TFTS).
Modules
saved_model_utils module: Convenience functions for working with time series saved_models.
Classes
class ARModel: Auto-regressive model, both linear and non-linear.
class ARRegressor: An Estimator for an (optionally non-linear) autoregressive model.
class CSVReader: Reads from a collection of CSV-formatted files.
class FilteringResults: Keys returned from evaluation/filtering.
class NumpyReader: A time series parser for feeding Numpy arrays to a TimeSeriesInputFn.
class OneShotPredictionHead: A time series head which exports a single stateless serving signature.
class RandomWindowInputFn: Wraps a TimeSeriesReader to create random batches of windows.
class StructuralEnsembleRegressor: An Estimator for structural time series models.
class TimeSeriesRegressor: An Estimator to fit and evaluate a time series model.
class TrainEvalFeatures: Feature names used during training and evaluation.
class WholeDatasetInputFn: Supports passing a full time series to a model for evaluation/inference.
Functions
predict_continuation_input_fn(...): An Estimator input_fn for running predict() after evaluate().