TPOT is built on top of several existing Python libraries, including:
Most of the necessary Python packages can be installed via the Anaconda Python distribution, which we strongly recommend that you use. We also strongly recommend that you use of Python 3 over Python 2 if you're given the choice.
NumPy, SciPy, scikit-learn, pandas and joblib can be installed in Anaconda via the command:
conda install numpy scipy scikit-learn pandas joblib
DEAP, tqdm and stopit can be installed with pip
via the command:
pip install deap tqdm stopit
Optionally, you can install XGBoost if you would like TPOT to use the eXtreme Gradient Boosting models. XGBoost is entirely optional, and TPOT will still function normally without XGBoost if you do not have it installed. Windows users: pip installation may not work on some Windows environments, and it may cause unexpected errors.
pip install xgboost
If you have issues installing XGBoost, check the XGBoost installation documentation.
If you plan to use Dask for parallel training, make sure to install dask[delay] and dask[dataframe] and dask_ml.
pip install dask[delayed] dask[dataframe] dask-ml fsspec>=0.3.3
If you plan to use the TPOT-MDR configuration, make sure to install scikit-mdr and scikit-rebate:
pip install scikit-mdr skrebate
Finally to install TPOT itself, run the following command:
pip install tpot
Please file a new issue if you run into installation problems.