Transactions on Rough Sets I James F. Peters - Andrzej Skowron, Editors-in-Chief / [electronic resource] :
edited by James F. Peters, Andrzej Skowron, Jerzy W. Grzymała-Busse, Bożena Kostek, Roman W. Świniarski, Marcin S. Szczuka.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 2004.
- X, 406 p. online resource.
- Lecture Notes in Computer Science, 3100 0302-9743 ; .
- Lecture Notes in Computer Science, 3100 .
Rough Sets – Introduction -- Some Issues on Rough Sets -- Rough Sets – Theory -- Learning Rules from Very Large Databases Using Rough Multisets -- Data with Missing Attribute Values: Generalization of Indiscernibility Relation and Rule Induction -- Generalizations of Rough Sets and Rule Extraction -- Towards Scalable Algorithms for Discovering Rough Set Reducts -- Variable Precision Fuzzy Rough Sets -- Greedy Algorithm of Decision Tree Construction for Real Data Tables -- Consistency Measures for Conflict Profiles -- Layered Learning for Concept Synthesis -- Basic Algorithms and Tools for Rough Non-deterministic Information Analysis -- A Partition Model of Granular Computing -- Rough Sets – Applications -- Musical Phrase Representation and Recognition by Means of Neural Networks and Rough Sets -- Processing of Musical Metadata Employing Pawlak’s Flow Graphs -- Data Decomposition and Decision Rule Joining for Classification of Data with Missing Values -- Rough Sets and Relational Learning -- Approximation Space for Software Models -- Application of Rough Sets to Environmental Engineering Models -- Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients -- Independent Component Analysis, Principal Component Analysis and Rough Sets in Face Recognition.
9783540277941
10.1007/b98175 doi
Computer science.
Database management.
Artificial intelligence.
Computer vision.
Optical pattern recognition.
Computer Science.
Computation by Abstract Devices.
Mathematical Logic and Formal Languages.
Artificial Intelligence (incl. Robotics).
Database Management.
Pattern Recognition.
Image Processing and Computer Vision.
QA75.5-76.95
004.0151
Rough Sets – Introduction -- Some Issues on Rough Sets -- Rough Sets – Theory -- Learning Rules from Very Large Databases Using Rough Multisets -- Data with Missing Attribute Values: Generalization of Indiscernibility Relation and Rule Induction -- Generalizations of Rough Sets and Rule Extraction -- Towards Scalable Algorithms for Discovering Rough Set Reducts -- Variable Precision Fuzzy Rough Sets -- Greedy Algorithm of Decision Tree Construction for Real Data Tables -- Consistency Measures for Conflict Profiles -- Layered Learning for Concept Synthesis -- Basic Algorithms and Tools for Rough Non-deterministic Information Analysis -- A Partition Model of Granular Computing -- Rough Sets – Applications -- Musical Phrase Representation and Recognition by Means of Neural Networks and Rough Sets -- Processing of Musical Metadata Employing Pawlak’s Flow Graphs -- Data Decomposition and Decision Rule Joining for Classification of Data with Missing Values -- Rough Sets and Relational Learning -- Approximation Space for Software Models -- Application of Rough Sets to Environmental Engineering Models -- Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients -- Independent Component Analysis, Principal Component Analysis and Rough Sets in Face Recognition.
9783540277941
10.1007/b98175 doi
Computer science.
Database management.
Artificial intelligence.
Computer vision.
Optical pattern recognition.
Computer Science.
Computation by Abstract Devices.
Mathematical Logic and Formal Languages.
Artificial Intelligence (incl. Robotics).
Database Management.
Pattern Recognition.
Image Processing and Computer Vision.
QA75.5-76.95
004.0151