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Second Case Study: Inference of Diagnostic Rules for Breast Cancer

In: Data Mining and Knowledge Discovery via Logic-Based Methods

Author

Listed:
  • Evangelos Triantaphyllou

    (Louisiana State University)

Abstract

For this case study we used a data set that described a number of clinical cases of breast cancer diagnoses. The data were divided into two disjoint sets of malignant and sub benign case benign cases. We applied the sub OCAT (one clause at a time) approach OCAT approach, as it is embedded in the RA1 heuristic (see also Chapter 4), after the data were transformed into binary ones according to the method described in Section 2.2. The following sections describe the data and inferred sub diagnostic rules diagnostic rules in more detail.

Suggested Citation

  • Evangelos Triantaphyllou, 2010. "Second Case Study: Inference of Diagnostic Rules for Breast Cancer," Springer Optimization and Its Applications, in: Data Mining and Knowledge Discovery via Logic-Based Methods, chapter 0, pages 289-296, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-1630-3_15
    DOI: 10.1007/978-1-4419-1630-3_15
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