Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Chapter 1 A Common Logic Approach to Data Mining and Pattern Recognition

Chapter 2 The One Clause at a Time (OCAT) Approach to Data Mining and Knowledge Discovery

Chapter 3 An Incremental Learning Algorithm for Inferring Logical Rules from Examples in the Framework of the Common Reasoning Process

Chapter 4 Discovering Rules That Govern Monotone Phenomena

Chapter 5 Learning Logic Formulas and Related Error Distributions

Chapter 6 Feature Selection for Data Mining

Chapter 7 Transformation of Rational Data and Set Data to Logic Data

Chapter 8 Data Farming: Concepts and Methods

Chapter 9 Rule Induction Through Discrete Support Vector Decision Trees

Chapter 10 Multi-Attribute Decision Trees and Decision Rules

Chapter 11 Knowledge Acquisition and Uncertainty in Fault Diagnosis: A Rough Sets Perspective

Chapter 12 Discovering Knowledge Nuggets with a Genetic Algorithm

Chapter 13 Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Chapter 14 Fuzzy Logic in Discovering Association Rules: An Overview

Chapter 15 Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview

Chapter 16 Data Mining from Multimedia Patient Records

Chapter 17 Learning to Find Context Based Spelling Errors

Chapter 18 Induction and Inference with Fuzzy Rules for Textual Information Retrieval

Chapter 19 Statistical Rule Induction in the Presence of Prior Information: The Bayesian Record Linkage Problem

Chapter 20 Some Future Trends in Data Mining