Data Mining and Knowledge Discovery via Logic-Based Methods: Theory, Algorithms, and Applications

Front Matter....Pages i-xxxiii
Front Matter....Pages 1-1
Introduction....Pages 3-20
Inferring a Boolean Function from Positive and Negative Examples....Pages 21-56
A Revised Branch-and-Bound Approach for Inferring a Boolean Function from Examples....Pages 57-72
Some Fast Heuristics for Inferring a Boolean Function from Examples....Pages 73-100
An Approach to Guided Learning of Boolean Functions....Pages 101-123
An Incremental Learning Algorithm for Inferring Boolean Functions....Pages 125-145
A Duality Relationship Between Boolean Functions in CNF and DNF Derivable from the Same Training Examples....Pages 147-150
The Rejectability Graph of Two Sets of Examples....Pages 151-170
Front Matter....Pages 171-171
The Reliability Issue in Data Mining: The Case of Computer-Aided Breast Cancer Diagnosis....Pages 173-190
Data Mining and Knowledge Discovery by Means of Monotone Boolean Functions....Pages 191-227
Some Application Issues of Monotone Boolean Functions....Pages 229-239
Mining of Association Rules....Pages 241-255
Data Mining of Text Documents....Pages 257-276
First Case Study: Predicting Muscle Fatigue from EMG Signals....Pages 277-287
Second Case Study: Inference of Diagnostic Rules for Breast Cancer....Pages 289-296
A Fuzzy Logic Approach to Attribute Formalization: Analysis of Lobulation for Breast Cancer Diagnosis....Pages 297-308
Conclusions....Pages 309-315
Back Matter....Pages 317-350