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1. Enriched Discretisation: Information Fusion from Supervised and Unsupervised Processing

2. Decision Trees with Hypotheses for Recognition of Monotone Boolean Functions and for Sorting

3. Greedy Algorithms for Decision Trees with Hypotheses

4. Multi-heuristic Induction of Decision Rules

5. Attribute Relevance and Discretisation in Knowledge Discovery: A Study in Stylometric Domain

6. Infinite Families of Concepts

11. Introduction

12. Main Notions

21. Importance of Characteristic Features and Their Form for Data Exploration.

23. Introduction

29. Main Notions

35. Optimization of Decision Rules Relative to Length - Comparative Study

40. On Combining Discretisation Parameters and Attribute Ranking for Selection of Decision Rules

42. Optimization of Approximate Decision Rules Relative to Length

43. Application of Greedy Heuristics for Feature Characterisation and Selection: A Case Study in Stylometric Domain

47. Greedy Algorithm for the Construction of Approximate Decision Rules for Decision Tables with Many-Valued Decisions

50. Sequential Optimization of -Decision Rules Relative to Length, Coverage and Number of Misclassifications

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