PyDTA (Arxiv Paper)
It is recommended to install this library inside a virtual enviroment, since it requires many other libraries with specific versions. It is enough to run pip installer, it will install all dependencies.
pip3 install pydta
This module contains the definition of DTA models presented in our paper. The weak learners are also implemented in this module.
This module implements data related functions and classes. You can also find a sample DTA dataset here.
This module contains the implementation of metrics used in the paper, which are rmse, mse, r2 and ci.
This module contains helper functions.
You can check out the ipynb notebook named "pydata samples.ipynb" where you can find 4 sample usages of this library.