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Heterogeneous Oblique Double Random Forest. (arXiv:2304.06788v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
The decision tree ensembles use a single data feature at each node for
splitting the data. However, splitting in this manner may fail to capture the
geometric properties of the data. Thus, oblique decision trees generate the
oblique hyperplane for splitting the data at each non-leaf node. Oblique
decision trees capture the geometric properties of the data and hence, show
better generalization. The performance of the oblique decision trees depends on
the way oblique hyperplanes are generate and the data …
arxiv classifiers data decision decision trees feature hyperplane multiple node performance random tree trees