Installation#

It is recommended to use pip or conda for installation. Please make sure the latest version is installed, as PyOD is updated frequently:

pip install pyod            # normal install
pip install --upgrade pyod  # or update if needed

conda install -c conda-forge pyod

Alternatively, you could clone and run setup.py file:

git clone https://github.com/yzhao062/pyod.git
cd pyod
pip install .

Required Dependencies:

  • Python 3.6+

  • joblib

  • matplotlib

  • numpy>=1.19

  • numba>=0.51

  • scipy>=1.5.1

  • scikit_learn>=0.20.0

  • six

Optional Dependencies (see details below):

  • combo (optional, required for models/combination.py and FeatureBagging)

  • keras/tensorflow (optional, required for AutoEncoder, and other deep learning models)

  • pandas (optional, required for running benchmark)

  • suod (optional, required for running SUOD model)

  • xgboost (optional, required for XGBOD)

  • pythresh to use thresholding

Warning

PyOD has multiple neural network based models, e.g., AutoEncoders, which are implemented in both Tensorflow and PyTorch. However, PyOD does NOT install these deep learning libraries for you. This reduces the risk of interfering with your local copies. If you want to use neural-net based models, please make sure these deep learning libraries are installed. Instructions are provided: neural-net FAQ. Similarly, models depending on xgboost, e.g., XGBOD, would NOT enforce xgboost installation by default.