Why Do Tree Ensemble Approximators Not Outperform the Recursive-Rule eXtraction Algorithm?
Soma Onishi; Masahiro Nishimura; Ryota Fujimura; Yoichi Hayashi · 2024 · Machine Learning and Knowledge Extraction
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Although machine learning models are widely used in critical domains, their complexity and poor interpretability remain problematic. Decision trees (DTs) and rule-based models are known for their interpretability, and numerous studies have…
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Metadata source: Crossref · DOI 10.3390/make6010031