4 papers
Extremely Simple Streaming Forest
Haoyin Xu, Jayanta Dey, Sambit Panda +1
Decision forests, including random forests and gradient boosting trees, remain the leading machine learning methods for many real-world data problems, especially on tabular data. H…
Learning Interpretable Characteristic Kernels via Decision Forests
Sambit Panda, Cencheng Shen, Joshua T. Vogelstein
Decision forests are widely used for classification and regression tasks. A lesser known property of tree-based methods is that one can construct a proximity matrix from the tree(s…
Universally Consistent K-Sample Tests via Dependence Measures
Sambit Panda, Cencheng Shen, Ronan Perry +4
The K-sample testing problem involves determining whether K groups of data points are each drawn from the same distribution. Analysis of variance is arguably the most classical met…
hyppo: A Multivariate Hypothesis Testing Python Package
Sambit Panda, Satish Palaniappan, Junhao Xiong +4
We introduce hyppo, a unified library for performing multivariate hypothesis testing, including independence, two-sample, and k-sample testing. While many multivariate independence…