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ZIP Tree for Zero-Inflated Data Analysis by Alex Miller is a document available to read on EtoBox.

What is ZIP Tree for Zero-Inflated Data Analysis about?

This document proposes a new decision tree method called the Zero-Inflated Poisson (ZIP) tree for analyzing zero-inflated count data. The ZIP tree modifies CART by using the maximum zero-inflated Poisson likelihood as the split criterion, rather than variance reduction, to find the best split. Simulation results and an analysis of a real-world soldering defect dataset are presented to investigate the properties and performance of the ZIP tree compared to CART. The ZIP tree may provide a more efficient appro

Author

Alex Miller

Language

EN