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Analyze Additive and Interaction Effects via Collaborative Trees
We present Collaborative Trees, a novel tree model designed for regression prediction, along with its bagging version, which aims to analyze complex statistical associations between features and uncover potential patterns inherent in the data.
FACT: High-Dimensional Random Forests Inference
Quantifying the usefulness of individual features in random forests learning can greatly enhance its interpretability.
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