Time series Framework
Project description
Context
TSBoost is a framework for time series forecasting.
It mixes classical statistics practices with non linear optimisation techniques of current Machine Learning.
Requirements
32-bit Python is not supported. Please install 64-bit version.
TSBoost uses gradient boosting optimisation provided by XGBoost & LightGBM, both have C++ source code and need a compiler.
For Windows users, VC runtime is needed if Visual Studio (2015 or newer) is not installed.
For Linux users, glibc >= 2.14 is required
sudo apt-get install build-essential # Ubuntu/Debian
sudo yum groupinstall ‘Development Tools’ # CentOS/RHEL
For macOS users, install OpenMP librairy
brew install libomp
Installation
After installing the compiler, install from PyPI Using pip
pip install tsboost
Quick Start
You can get started with a jupyter notebook tutorial : TSBoot quick start
History
0.1.0 (2019-06-10)
First release on PyPI.
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