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szilard / benchm-ml

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
MIT License
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Integer encoding for categorical variables in random forests in R #22

Closed zachmayer closed 8 years ago

zachmayer commented 8 years ago

This quote stuck out to me:

It cannot cope by default with a large number of categories, therefore the data had to be one-hot encoded.

Did you try integer-encoding categories? It looks like you did for python, maybe that's worth trying with R.

szilard commented 8 years ago

Yes, I played around, see the discussion here https://github.com/szilard/benchm-ml/issues/1

szilard commented 8 years ago

Closing this, but let me know if you have further questions.