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Fuzzy-Rough Instance Selection

Fuzzy-Rough Instance Selection. Outline. The importance of instance selection Rough set theory Fuzzy-rough sets Fuzzy-rough instance selection Experimentation Conclusion. Instance selection. Knowledge discovery The problem of too much data Requires storage

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Fuzzy-Rough Instance Selection

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  1. Fuzzy-Rough Instance Selection

  2. Outline • The importance of instance selection • Rough set theory • Fuzzy-rough sets • Fuzzy-rough instance selection • Experimentation • Conclusion

  3. Instance selection • Knowledge discovery • The problem of too much data • Requires storage • Intractable for data mining algorithms • Removing data that is noisy or irrelevant

  4. Rough set theory Upper Approximation Set A Lower Approximation Equivalence class Rx Rx is the set of all points that are indiscerniblewith point x

  5. Fuzzy-rough sets • Approximate equality • Handle real-valued features via fuzzy tolerance relations instead of crisp equivalence • Better noise and uncertainty handling • Focus has been on feature selection, not instance selection

  6. Fuzzy-rough sets • Parameterized relation • Fuzzy-rough definitions:

  7. Instance selection: basic idea Not needed Remove objects to keep the underlying approximations unchanged

  8. Instance selection: basic idea Remove objects to keep the underlying approximations unchanged

  9. FRIS-I

  10. FRIS-II

  11. FRIS-III

  12. Experimentation: setup

  13. Results: FRIS-I (heart) • (214 objects, 9 features)

  14. Results: FRIS-II (heart)

  15. Results: FRIS-III (heart)

  16. Conclusion • Proposed new techniques for instance selection based on fuzzy-rough sets • Managed to reduce the number of instances significantly, retaining classification accuracy • Future work • Many possibilities for novel fuzzy-rough instance selection methods • Comparisons with non-rough techniques • Improving the complexity of FRIS-III • Combined instance/feature selection

  17. WEKA implementations of all fuzzy-rough methods can be downloaded from: • http://users.aber.ac.uk/rkj/book/weka.zip

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