The goal of hhcartr is to provide an implementation in R of the HHCART(G) algorithm. HHCART(G) is an oblique decision tree learning algorithm. HHCART(G) combines learning concepts from two classification tree algorithms, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that utilizes reflected feature spaces for node splitting. Training examples are reflected to align linear structure in the data with a coordinate axes. Searching axis-parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. This version of the package (v1.0.0) is a sequential R implementation and is primarily a research tool. Future versions will introduce parallelization using C++.
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