Heterogeneous oblique random forest
Decision trees in random forests use a single feature in non-leaf nodes to split the data. Such splitting results in axis-parallel decision boundaries which may fail to exploit the geometric structure in the data. In oblique decision trees, an oblique hyperplane is employed instead of an axis-parall...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/138843 |
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Institution: | Nanyang Technological University |
Language: | English |