Decision tree post-pruning without loss of accuracy using the SAT-PP algorithm with an empirical evaluation on clinical data

Teddy Lazebnik,Svetlana Bunimovich-Mendrazitsky

doi:10.1016/j.datak.2023.102173

Decision tree post-pruning without loss of accuracy using the SAT-PP algorithm with an empirical evaluation on clinical data

Teddy Lazebnik, Svetlana Bunimovich-Mendrazitsky

https://doi.org/10.1016/j.datak.2023.102173

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Journal: Data & Knowledge Engineering	Publication Date: Mar 4, 2023
Citations: 10

Affiliation: University College London, Ariel University

#Post Pruning #Decision Tree Model #Decision Tree #Techniques In Data Mining #Loss Of Accuracy #Boolean Satisfiability #Clinical Domain #Tree Size #Accuracy Of Classification #Worse Performance

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Decision tree post-pruning without loss of accuracy using the SAT-PP algorithm with an empirical evaluation on clinical data