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Batch effects, undesirable sources of variance across multiple experiments, present a substantial hurdle for scientific and clinical …

Decision forests, including random forests and gradient boosting trees, remain the leading machine learning methods for many real-world …

Deep networks and decision forests (such as random forests and gradient boosted trees) are the leading machine learning methods for …

We introduce hyppo, a unified library for performing multivariate hypothesis testing, including independence, two-sample, and k-sample …

The $k$-sample testing problem tests whether or not $k$ groups of data points are sampled from the same distribution. Multivariate …

Decision forests are popular tools for classification and regression. These forests naturally produce proximity matrices measuring how …