On Testing Decision Tree

Authors Nader H. Bshouty, Catherine A. Haddad-Zaknoon

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Nader H. Bshouty
  • Department of Computer Science, Technion, Haifa, Israel
Catherine A. Haddad-Zaknoon
  • Department of Computer Science, Technion, Haifa, Israel

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Nader H. Bshouty and Catherine A. Haddad-Zaknoon. On Testing Decision Tree. In 39th International Symposium on Theoretical Aspects of Computer Science (STACS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 219, pp. 17:1-17:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


In this paper, we study testing decision tree of size and depth that are significantly smaller than the number of attributes n. Our main result addresses the problem of poly(n,1/ε) time algorithms with poly(s,1/ε) query complexity (independent of n) that distinguish between functions that are decision trees of size s from functions that are ε-far from any decision tree of size ϕ(s,1/ε), for some function ϕ > s. The best known result is the recent one that follows from Blanc, Lange and Tan, [Guy Blanc et al., 2020], that gives ϕ(s,1/ε) = 2^{O((log³s)/ε³)}. In this paper, we give a new algorithm that achieves ϕ(s,1/ε) = 2^{O(log² (s/ε))}. Moreover, we study the testability of depth-d decision tree and give a distribution free tester that distinguishes between depth-d decision tree and functions that are ε-far from depth-d² decision tree.

Subject Classification

ACM Subject Classification
  • Theory of computation → Oracles and decision trees
  • Testing decision trees


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