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Install

Installation

EmpiricML is available on PyPI and can be installed using pip:

pip install empiricml

Requirements: Python 3.11 or higher.

Dependencies

When you install EmpiricML, the following dependencies will be automatically installed:

  • numpy>=1.26.4
  • pandas>=2.2.2
  • pyarrow>=15.0.2
  • polars>=1.31.0
  • matplotlib>=3.9.0
  • scikit-learn>=1.7.1
  • lightgbm>=4.6.0
  • xgboost>=3.1.2
  • catboost>=1.2.8
  • skorch>=1.3.1

PyTorch Support

EmpiricML supports PyTorch models through the TorchWrapper class. However, PyTorch is not installed automatically to allow users to choose the specific version that matches their hardware configuration (CPU vs GPU, CUDA version, etc.).

To use PyTorch models with EmpiricML:

  1. Install PyTorch separately by following the instructions on the official PyTorch website.
  2. Use the TorchWrapper class to integrate your PyTorch models into the EmpiricML workflow.