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Random forest algorithms with different types of information gain based on deformed entropies.

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hse-scila/random_forest_project

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Random forests with parametric entropy-based information gains.

Random forest algorithms with different types of information gain based on deformed entropies. Jupyter notebooks (ipynb) contain codes for building random forests with different types of information gain.

  • "ClassificationRandomForest.ipynb" builds random forest for a classification task
  • "RegressionRandomForest.ipynb" builds random forest for a regression task
  • "Breiman_and_LinearRegression.ipynb" containes baseline models for a regression task, namely, Breiman's random forest and multiple linear regression.

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Random forest algorithms with different types of information gain based on deformed entropies.

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