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Constructing Efficient Decision Trees by Using Optimized Numeric Association Rules

Summary: Extends Quinlan’s entropy-based decision-tree induction by mining 2D association rules on numeric attribute pairs and selecting the entropy-minimizing region split to address strong correlations. Provides efficient algorithms for x-monotone connected, base-monotone, rectangular, and rectilinear-convex regions; SONAR implementation yields compact trees. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8339
Venue
VLDB
Year
1996
Pagerank
6.7779074e-05
Overall Rank
3,770 | 73.78%
DOI
-

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