Ebook: Transactions on Rough Sets IV

Volume IV of the Transactions on Rough Sets (TRS) introduces a number of new advances in the theory and application of rough sets. Rough sets and - proximationspaceswereintroducedmorethan30yearsagobyZdzis lawPawlak. These advances have profound implications in a number of research areas such as the foundations of rough sets, approximate reasoning, arti?cial intelligence, bioinformatics,computationalintelligence, cognitivescience, intelligentsystems, datamining,machineintelligence,andsecurity. Inaddition,itisevidentfromthe papers included in this volume that the foundations and applications of rough sets is a very active research area worldwide. A total of 16 researchers from 7 countries are represented in this volume, namely, Canada, India, Norway, S- den, Poland, Russia and the United States of America. Evidence of the vigor, breadth and depth of research in the theory and applications of rough sets can be found in the 10 articles in this volume. Prof. Pawlak has contributed a treatise on the philosophical underpinnings of rough sets. In this treatise, observations are made about the Cantor notion of a set, antinomies arising from Cantor sets, the problem of vagueness (es- cially, vague (imprecise) concepts), fuzzy sets, rough sets, fuzzy vs. rough sets as well as logic and rough sets. Among the many vistas and research directions suggested by Prof. Pawlak, one of the most fruitful concerns the model for a rough membership function, which was incarnated in many di?erent forms since its introduction by Pawlakand Skowronin 1994. Recall, here, that Prof.

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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.

This fourth volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Seven papers explore the theory of rough sets in various domains: a framework for reasoning with rough sets utilizing extended logic programs, optimization of decision trees, fuzzy set and rough set approaches to dealing with missing data, generalization of the indiscernibility relation as an aid to dealing with incompletely specified decision tables, deterministic and non-deterministic decision tree complexity in the context of both finite and infinite information systems, analogy-based reasoning in classifier construction, and incremental learning and evaluation of structures of rough decision tables. In addition, two papers in this volume introduce new applications of rough sets, namely, supervised learning in the gene ontology and the design of an intrusion detection system.

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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.

This fourth volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Seven papers explore the theory of rough sets in various domains: a framework for reasoning with rough sets utilizing extended logic programs, optimization of decision trees, fuzzy set and rough set approaches to dealing with missing data, generalization of the indiscernibility relation as an aid to dealing with incompletely specified decision tables, deterministic and non-deterministic decision tree complexity in the context of both finite and infinite information systems, analogy-based reasoning in classifier construction, and incremental learning and evaluation of structures of rough decision tables. In addition, two papers in this volume introduce new applications of rough sets, namely, supervised learning in the gene ontology and the design of an intrusion detection system.

Content:
Front Matter....Pages -
A Treatise on Rough Sets....Pages 1-17
On Optimization of Decision Trees....Pages 18-36
Dealing with Missing Data: Algorithms Based on Fuzzy Set and Rough Set Theories....Pages 37-57
Characteristic Relations for Incomplete Data: A Generalization of the Indiscernibility Relation....Pages 58-68
Supervised Learning in the Gene Ontology Part I: A Rough Set Framework....Pages 69-97
Supervised Learning in the Gene Ontology Part II: A Bottom-Up Algorithm....Pages 98-124
Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach....Pages 125-143
A Fast Host-Based Intrusion Detection System Using Rough Set Theory....Pages 144-161
Incremental Learning and Evaluation of Structures of Rough Decision Tables....Pages 162-177
A Framework for Reasoning with Rough Sets....Pages 178-276
Analogy-Based Reasoning in Classifier Construction....Pages 277-374
Back Matter....Pages -

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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.

This fourth volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Seven papers explore the theory of rough sets in various domains: a framework for reasoning with rough sets utilizing extended logic programs, optimization of decision trees, fuzzy set and rough set approaches to dealing with missing data, generalization of the indiscernibility relation as an aid to dealing with incompletely specified decision tables, deterministic and non-deterministic decision tree complexity in the context of both finite and infinite information systems, analogy-based reasoning in classifier construction, and incremental learning and evaluation of structures of rough decision tables. In addition, two papers in this volume introduce new applications of rough sets, namely, supervised learning in the gene ontology and the design of an intrusion detection system.

Content:
Front Matter....Pages -
A Treatise on Rough Sets....Pages 1-17
On Optimization of Decision Trees....Pages 18-36
Dealing with Missing Data: Algorithms Based on Fuzzy Set and Rough Set Theories....Pages 37-57
Characteristic Relations for Incomplete Data: A Generalization of the Indiscernibility Relation....Pages 58-68
Supervised Learning in the Gene Ontology Part I: A Rough Set Framework....Pages 69-97
Supervised Learning in the Gene Ontology Part II: A Bottom-Up Algorithm....Pages 98-124
Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach....Pages 125-143
A Fast Host-Based Intrusion Detection System Using Rough Set Theory....Pages 144-161
Incremental Learning and Evaluation of Structures of Rough Decision Tables....Pages 162-177
A Framework for Reasoning with Rough Sets....Pages 178-276
Analogy-Based Reasoning in Classifier Construction....Pages 277-374
Back Matter....Pages -
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