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KDD97-020.pdf
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🔗 Source: cdn.aaai.org
📊 Size: 569 KB
👤 Author: Bayardo Jr., Roberto J.
⬇️ Downloads: 69

Summary

The approach effectively extracts high-confidence classification rules from several classification benchmarks. The technique is useful for understanding relationships between instance features and their class, and the rules produced can be exploited by tree-inducers to select better split points. The paper demonstrates that the enhanced association rule miner is remarkably effective at identifying rules that classify most data with high confidence, often without any heuristic pruning.

Description

The approach effectively extracts high-confidence classification rules from several classification benchmarks.

Technical Information

  • File Format: PDF
  • File Size: 569 KB
  • Pages: 4
  • Language: EN
  • Author: Bayardo Jr., Roberto J.
  • Total Downloads: 69
  • Last Updated: 4 days ago

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