HTT

A novel decision tree algorithm in the hypothesis testing framework. The algorithm examines the distribution difference between two child nodes over all possible binary partitions. The test statistic of the hypothesis testing is equivalent to the generalized energy distance, which enables the algorithm to be more powerful in detecting the complex structure, not only the mean difference. It is applicable for numeric, nominal, ordinal explanatory variables and the response in general metric space of strong negative type. The algorithm has superior performance compared to other tree models in type I error, power, prediction accuracy, and complexity.

Last 30 days

This package has been downloaded 210 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 15 times.

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Last 365 days

This package has been downloaded 2,332 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 24, 2024 with 26 downloads.

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