The bsnsing package provides functions for building a decision tree classifier and making predictions. It solves the two-class and multi-class classification problems under the supervised learning paradigm. While building a decision tree, bsnsing uses a Boolean rule involving multiple variables to split a node. Each split rule is identified by solving an optimization model that minimizes misclassification as well as complexity. Compared to other decision tree learners that seek single-variable splits in a greedy fashion, bsnsing's approach is more holistic and produces highly interpretable and accurate trees.
|Maintainer||Yanchao Liu <[email protected]>|
|Package repository||View on GitHub|
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