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🐫 Python Comparative Analysis for Machine Learning 🐫

pycaML is an easy machine learning model comparison tool with optimization. It allows to generate a table comparing multiple machine learning models, to see which one is best for your data. The unique feature of pycaML is built-in hyperparameters tuning using Bayesian Optimization. It also supports meta-models like Stacking and Voting ensembles. You can setup and optimize 25 models with one line of code.

Installation

python pip install pycaML

Usage

Check out the example notebook.

Key Features

  • Compare up to 25 different models with one line of code
  • Hyperparameters tuning with built-in search spaces
  • Stacking and Voting models support
  • Automatic train-test split
  • Built-in cross validation
  • Saves every result in a nice .csv table

Version

pycaML is in early development, in the future many features are planned to be added.

Author

If you like the package, you can find me on LinkedIn.