0407ebf5c3
* Remove manually-added bold style for titles in [User guide] section * Fix failed relative links in windows user guide * Remove manually-added bold style for titles in [Orca] section * Fix failed relative links & title bold fix in Nano 5 min * Remove manually-added bold style for titles in [Nano] section * Remove manually-added bold style for titles in [DLlib] section * Remove manually-added bold style for titles in [Chronos] section * Remove manually-added bold style for titles in Developer guide * Remove manually-added bold title style for all other not-included md files in docs/readthedocs/source/doc folder * Fix based on comments
1.3 KiB
Synthetic Data Generation
Chronos provides simulators to generate synthetic time series data for users who want to conquer limited data access in a deep learning/machine learning project or only want to generate some synthetic data to play with.
.. note::
``DPGANSimulator`` is the only simulator chronos provides at the moment, more simulators are on their way.
1. DPGANSimulator
DPGANSimulator adopt DoppelGANger raised in Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions. The method is data-driven unsupervised method based on deep learning model with GAN (Generative Adversarial Networks) structure. The model features a pair of seperate attribute generator and feature generator and their corresponding discriminators DPGANSimulator also supports a rich and comprehensive input data (training data) format and outperform other algorithms in many evalution metrics.
.. note::
We reimplement this model by pytorch(original implementation was based on tf1) for better performance(both speed and memory).
Users may refer to detailed API doc.