- Email: [email protected]
The asymmetrical brain
980
Rook
REPORTS
The Enterprise of Science in Islam: New Perspectives. Edited by Jan P. Hogendijk and Abdelhamid I. Sabra. The MIT Press, Cambridge. MA. (2003). 386 pages. $45.00. Contents: Introduction. Contributors. I. Cross-cultural transmission. I, The transmission of Hindu-Arabic numerals reconsidered (Paul Kunitzsch). 2. The transmission of Arabic astronomy via Antioch and Pisa in the second quarter of the twelfth century. (Charles Burnett). II. Transformations of Greek optics. 3. The many aspects of “appearances”: Arabic optics to 950 AD (Elaheh Kheirandish). 4. Ibn al-Haytham’s revolutionary project in optics: The achievement and the obstacle (A.I. Sabra). III. Mathematics: Philosophy and practice. 5. Mathematics and philosophy in medieval Islam (Gerhard Endress). 6. Tenth-century mathematics through the eyes of Abii Sahl al-Kiihi (J. Lennart Berggren). IV. Numbers, geometry, and architecture. 7. Quadratus mirabilis (Jacques Sesiano). 8. Calculating surface areas and volumes in Islamic architecture (Yvonne Dold-Samplonius). V. Seventeenth-century transmission of astronomy. 9. The Sarvasiddhantartiju of Nityananda (David Pingree). 10. On the lunar tables in Sanjaq Dar’s 29 aMhan (Julio Samso). VI. Science and medicine in the Maghrib and al-Andalus. 11. A panorama of research on the history of mathematics in al-Andalus and the Maghrib between the ninth and sixteenth centuries (Ahmed Djebbar). 12. Another Andalusian revolt? Ibn Rushd’s critique of al-Dindi’s Pharmacological Computus (Y. Tzvi Langermann). Index. Exploratory Data Mining and Data Cleaning. By Tamraparni Dasu and Theodore Johnson. John Wiley & Sons, Hoboken, NJ. 203 pages. $69.95. Contents: Preface. 1. Exploratory data mining and data cleaning: An overview. 2. Exploratory data mining. 3. Partitions and piecewise models, 4. Data quality. 5. Data quality: Techniques and algorithms. Bibliography. Index. Brain- Wise: Studies in Neurovhilosophy. By Patricia Smith Churchland. The (2002). 471 pages. $25.00. Contents: Preface. 1. Introduction. I. Metaphysics. 2. An introduction to metaphysics. 4. Consciousness. 5. Free will. II. Epistemology. 6. An introduction to epistemology. 8. How do brains learn? III. Religion. 9. Religion and the brain. Notes. References.
MIT
Press,
Cambridge,
MA.
3. Self and self-knowledge. 7. How do brains represent? Index.
Spinnina the Semantic Web:Bkwins the World Wide Web to its Full Potential. Edited by Dieter Fensel, James Hendler, Henry Lieberman and Wolfgang Wahlster. The MIT Press, Cambridge, MA. (2003). 479 pages. $40.00. Contents: Foreword (Tim Berners-Lee). 1. Introduction (Dieter Fensel, James Hendler, Henry Lieberman and Wolfgang Wahlster). I. Languages and ontologies. 2. SHOE: A blueprint for the semantic web (Jeff Heflin, James Hendler and Sean Luke). 3. DAML-ONT: An ontology language for the semantic web (Deborah L. McGuinness, Richard Fikes, Lynn Andrea Stein and James Hendler). 4. Ontologies and schema languages on the web (Michel Klein, Jeen Broekstra, Dieter Fensel, Frank van Harmelen and Ian Horror&). 5. UPML: The language and tool support for making the semantic web alive (Borys Omelayenko, Monica Crutizy, Dieter Fensel, Richard Benjamins, Bob Wielinga, Enrico Motta, Mark Musen and and Ying Ding). 6. Ontologies come of age (Deborah L. McGuinness). II. Knowledge support. 7. Sesame: An architecture for storing and querying RDF data and schema information (Jeen Broekstra, Arjohn Kampman and Frank van Harmelen). 8. Enabling task-centered knowledge support through semantic markup (Rob Jasper and Mike Uschold). 9. Knowledge mobility: Semantics for the web as a white knight for knowledge-based systems (Yolanda Gil). 10. Complex relationships for the semantic web (Sanjeev Thacker, Amit Sheth and Shuchi Patel). 11. SEmantic portAL: The SEAL approach (Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer and York Sure). III. Dynamic aspect. 12. Semantic gadgets: Ubiquitous computing meets the semantic web (Ora Lassila and Mark Adler). 13. Static and dynamic semantics of the web (Chritopher Frye, Mike Plusch and Henry Lieberman). 14. Semantic annotation for web content adaptation (Masahiro Hori). 15. Task-achieving agents on the world wide web (Austin Tate, Jeff Dalton, John Levine and Alex Nixon). Contributors. Index. The Asymmetrical Brain. Edited by Kenneth Hugdahl and Richard J. Davidson. The MIT Press, Cambridge, MA. (2003). 796 pages. $90.00. Contents: Preface. I. Animal models/basic functions. 1. Hemispheric asymmetry in the visual system of birds (Onur Giintiirkiin). 2. A hippocampal theory of cerebral lateralization (Akaysha C. Tang). 3. Stress and coping: Asymmetry of dopamine efferents within the prefrontal cortex (Craig W. Berridge, Rodrigo A. Espafia and Thomas A. Stalnaker). 4. The nature and determinants of handedness (Alan A, Beaton). II. Neuroimaging and brain stimulation studies. 5. Characterizing functional asymmetries with brain mapping (Karl J. Friston). 6. Anatomical brain asymmetries and their relevance for functional asymmetries (Lutz JLncke and Helmuth Steinmetz). 7. Transcranial magnetic stimulation studies of asymmetry of cognitive functions in the brain (Alvaro Pascual-Leone and Vincent Walsh). III. Visual laterality. 8. Interaction between the hemispheres and its implications for the processing capacity of the brain (Marie T. Banich). 9. Asymmetries in encoding spatial relations (Bruno Laeng, Christopher F.
BOOK
REPORTS
'.
981
Chabris and Stephen M. Kosslyn). 10. Complexities of interhemispheric communication in sensoimotor tasks r~+ vealed by high-density event-related potential mapping (Clifford D. Saron, John J. Foxe, Char’lbs E. Schroeder and Herber G. Vaughan, Jr.). IV. Auditory laterality. 11. Hemispheric asymmetries in the processing of tonal stimuli (Robert J. Zatorre). 12. Dichotic listening in the study of auditory laterality (Kenneth Hugdahl).’ 13. Effects of attention on hemispheric asymmetry (Daniel S. O’Leary). V. Emotional laterality. 14. The functional neuroimaging of human emotion: Asymmetric contributions of cortical and subcortical circuitryt(Diego Pizaagalli, Alexander J. Schakman and Richard J. Davidson). 15. Regional brain activity in anxiety and depression, cognition/emotion interaction, and emotion regulation (Wendy Heller, Nancy S. Koven and Gregory A. Miller). 16. The state and trait nature of frontal EEG ssyeet,v in emotion (James A. Coan and John J.B. Allen). VI. Neurological disorders. 17. Agenesis of the corpus callosum (Maryse Lassonde and Hannelore C. Sauerwein). 18. Developmental disorders: Dyslexia (Mark A. Eckert and Christiana M. Leonard). 19. Structural correlates of brain asymmetry: Studies in left-handed and dyslexic individuals (Michel Habib and Fabrice Robichon). VII. Psychiatric disorders. 20. Frontal and parietotemporal asymmetries in depressive disorders: Behavioral, electrophysiologic, and neuroimaging findings (Gerard E. Bruder). 21. The laterality of schizophrenia (Michael F. Green, Mark J. Sergi and Robert S. Kern). Cbntributors. Author index. Subject index. Learnina and Genemlisation: With Applications to Neural Networks. By M. Vidyasagar. Springer-Verlag, London. (2003). 488 pages. $119.00, EUR 99.95, SFR 166.00, GBP 60.00. Contents: Preface to the second edition. Preface to the first edition. 1. Introduction. 2. Preliminaries. 3. Problem formulations. 4. Vapnik-Chervonenkis, pseudoand fat-shattering dimensions. 5. Uniform convergence of empirical means. 6. Learning under a fixed probability measure. 7. Distribution-free learning. 8. Learning under an intermediate family of probabilities. 9. Alternate models of learning. 10. Applications to neural networks. 11. Applications to control systems. 12. Some open problems. Handbook of Data Minina and Knowledae Discovery. Edited by Willi Klasgen and Jan M. iytkow. Oxford University Press, New York. (2002). 1026 pages. $250.00. Contents: Foreword: Enhancing the intelligence of discovery systems (Herbert A. Simon). Foreword: Data mining coming of age (Gregory Piatetsky-Shapiro). Preface (Willi KlBsgen and Jan M. iytkow). Part I. Data mining and knowledge discovery. 1. Knowledge discovery in databases: The purpose, necessity, and challenges (Willi Kkisgen and Jan M. iytkow). 2. The knowledge discovery process (Willi Klijsgen and Jan M. iytkow). 3. Multidisciplinary contributions to knowledge discovery (Jan M. iytkow and Willi KBsgen). Part II. Fundamental concepts. 4. Types and forms of data (Willi Kliisgen). 5. Types and forms of knowledge (patterns). 5.1. Contingency tables (Jan M. iytkow). 5.2. Subgroup patterns (Willi KlBsgen). 5.3. Rules (Jan M. iytkow). 5.4. Decision trees (Jan M. iytkow). 5.5. Functional relations (Jan M. iytkow). 5.6. Clusters (Padhraic Smyth). 5.7. Taxonomies and concept hierarchies (Jan M. iytkow). 5.8. Probabilistic and causal networks (Clark Glymour). 5.9. Neural networks (Witold Pedrycz). 6. Data and knowledge in database systems. 6.1. Relational databases (Raghu Ramakrishnan). 6.2. Object-oriented databases (Klaus R. Dittrich and Anca Vaduva). 6.3. Multidimensional databases and online analytical processing (Surajit Chaudhuri and Umesh Dayal). 6.4. Deductive databases (Carlo Zaniolo). 6.5. Parallel databases (Shahram Ghandeharizadeh and Frank Sommers). 6.6. Distributed, heterogeneous, and federated databases (Witold Litwin). 6.7. Meta-data management (Klaus R. Dittrich and Anca Vaduva). 7. Logic perspective on data and knowledge (Lech Polkowski and Andrzej Skowron). 8. Statistics perspective on data and knowledge (David Madigan and Martha Nsson). 9. Rough sets perspective on data and knowledge (Andrzej Skowron, Jan Komorowski, Zdisislaw Pawlak and Lech Polkowski). 10. Fuzzy sets perspective on data and knowledge (Witold Pedrycz). 11. Search techniques (Weixiong Zhang). 12. Stages of the discovery process (Thomas Part III. The process of knowledge discovery in databases. Reinartz). 13. Data warehousing. 13.1. Data cleaning and loading (Tqby Bloom). 13.2. Warehouse administration (Wolfgang Lehner). 14. Data reduction. 14.1. Sampling (David Madigan and Martha Nason). 14.2. Feature selection (Hiroshi Motoda and Huan Liu). 14.3. Feature aggregation (Hiroshi Motoda and Huan Liu). 14.4. Discretization of numerical attributes (Jerzy W. Grzymala-Busse). 15. Data visualization for domain exploration. 15.1. Interactive statistical graphics (Graham J. Wills and Daniel Keim). 15.2. Highly multivariate interaction techniques (Martin Theus). 15.3. Geographical information systems (Martin Theus). 15.4. Animation techniques (Stephen G. Eick). 16. Data mining tasks and methods. 16.1. Classification. 16.1.1. The goal of classification (Hans-Hermann.Bock). 16.1.2. Classification methodology (Hans-Hermann Bock). 16.1.3. Decision-tree discovery (Ronny Kohavi and J. Ross Quinlan). 16.1.4. Decision rules (Willi KlGsgen). 16.1.5. Bayesian classification (Nir Friedman and Ronny Kohavi) 16.1.6. Nearest-neighbor approaches (Belur V. Dasarathy). 16.1.7. Regression (Robert Henery). 16.1.8. Neural network approaches (Andreas Niirnberger, Witold Pedrycz and Rudolf Kruse). 16.1.9. Multicriteria classification (Salvatore Greco, Benedetto Matarazzo and Roman Slowinski). 16.2. Rule discovery. 16.2.1. Rough set approaches for discovering rules and attribute dependencies (qojciech Ziarko). 16.2.2. Characteristic rules (Jiawei Han). 16.2.3. Association rules (Heikki Mannila). 16.2.4. Inductive logic programming approaches (S&o Dieroski). 16.3. Subgroup discovery. 16.3.1. Deviation analysis (Willi Kkisgen). 16.3.2. Change analysis (Willi KlGsgen). 16.3.3. Drill-down methods (Tejwansh S. Anand). 16.4. Equation fitting. 16.4.1. Methodology for equation fitting (Takashi Wsshio and Hiroshi Motoda). 16.4.2. Equation finders (Jan M.
Rook
REPORTS
The Enterprise of Science in Islam: New Perspectives. Edited by Jan P. Hogendijk and Abdelhamid I. Sabra. The MIT Press, Cambridge. MA. (2003). 386 pages. $45.00. Contents: Introduction. Contributors. I. Cross-cultural transmission. I, The transmission of Hindu-Arabic numerals reconsidered (Paul Kunitzsch). 2. The transmission of Arabic astronomy via Antioch and Pisa in the second quarter of the twelfth century. (Charles Burnett). II. Transformations of Greek optics. 3. The many aspects of “appearances”: Arabic optics to 950 AD (Elaheh Kheirandish). 4. Ibn al-Haytham’s revolutionary project in optics: The achievement and the obstacle (A.I. Sabra). III. Mathematics: Philosophy and practice. 5. Mathematics and philosophy in medieval Islam (Gerhard Endress). 6. Tenth-century mathematics through the eyes of Abii Sahl al-Kiihi (J. Lennart Berggren). IV. Numbers, geometry, and architecture. 7. Quadratus mirabilis (Jacques Sesiano). 8. Calculating surface areas and volumes in Islamic architecture (Yvonne Dold-Samplonius). V. Seventeenth-century transmission of astronomy. 9. The Sarvasiddhantartiju of Nityananda (David Pingree). 10. On the lunar tables in Sanjaq Dar’s 29 aMhan (Julio Samso). VI. Science and medicine in the Maghrib and al-Andalus. 11. A panorama of research on the history of mathematics in al-Andalus and the Maghrib between the ninth and sixteenth centuries (Ahmed Djebbar). 12. Another Andalusian revolt? Ibn Rushd’s critique of al-Dindi’s Pharmacological Computus (Y. Tzvi Langermann). Index. Exploratory Data Mining and Data Cleaning. By Tamraparni Dasu and Theodore Johnson. John Wiley & Sons, Hoboken, NJ. 203 pages. $69.95. Contents: Preface. 1. Exploratory data mining and data cleaning: An overview. 2. Exploratory data mining. 3. Partitions and piecewise models, 4. Data quality. 5. Data quality: Techniques and algorithms. Bibliography. Index. Brain- Wise: Studies in Neurovhilosophy. By Patricia Smith Churchland. The (2002). 471 pages. $25.00. Contents: Preface. 1. Introduction. I. Metaphysics. 2. An introduction to metaphysics. 4. Consciousness. 5. Free will. II. Epistemology. 6. An introduction to epistemology. 8. How do brains learn? III. Religion. 9. Religion and the brain. Notes. References.
MIT
Press,
Cambridge,
MA.
3. Self and self-knowledge. 7. How do brains represent? Index.
Spinnina the Semantic Web:Bkwins the World Wide Web to its Full Potential. Edited by Dieter Fensel, James Hendler, Henry Lieberman and Wolfgang Wahlster. The MIT Press, Cambridge, MA. (2003). 479 pages. $40.00. Contents: Foreword (Tim Berners-Lee). 1. Introduction (Dieter Fensel, James Hendler, Henry Lieberman and Wolfgang Wahlster). I. Languages and ontologies. 2. SHOE: A blueprint for the semantic web (Jeff Heflin, James Hendler and Sean Luke). 3. DAML-ONT: An ontology language for the semantic web (Deborah L. McGuinness, Richard Fikes, Lynn Andrea Stein and James Hendler). 4. Ontologies and schema languages on the web (Michel Klein, Jeen Broekstra, Dieter Fensel, Frank van Harmelen and Ian Horror&). 5. UPML: The language and tool support for making the semantic web alive (Borys Omelayenko, Monica Crutizy, Dieter Fensel, Richard Benjamins, Bob Wielinga, Enrico Motta, Mark Musen and and Ying Ding). 6. Ontologies come of age (Deborah L. McGuinness). II. Knowledge support. 7. Sesame: An architecture for storing and querying RDF data and schema information (Jeen Broekstra, Arjohn Kampman and Frank van Harmelen). 8. Enabling task-centered knowledge support through semantic markup (Rob Jasper and Mike Uschold). 9. Knowledge mobility: Semantics for the web as a white knight for knowledge-based systems (Yolanda Gil). 10. Complex relationships for the semantic web (Sanjeev Thacker, Amit Sheth and Shuchi Patel). 11. SEmantic portAL: The SEAL approach (Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer and York Sure). III. Dynamic aspect. 12. Semantic gadgets: Ubiquitous computing meets the semantic web (Ora Lassila and Mark Adler). 13. Static and dynamic semantics of the web (Chritopher Frye, Mike Plusch and Henry Lieberman). 14. Semantic annotation for web content adaptation (Masahiro Hori). 15. Task-achieving agents on the world wide web (Austin Tate, Jeff Dalton, John Levine and Alex Nixon). Contributors. Index. The Asymmetrical Brain. Edited by Kenneth Hugdahl and Richard J. Davidson. The MIT Press, Cambridge, MA. (2003). 796 pages. $90.00. Contents: Preface. I. Animal models/basic functions. 1. Hemispheric asymmetry in the visual system of birds (Onur Giintiirkiin). 2. A hippocampal theory of cerebral lateralization (Akaysha C. Tang). 3. Stress and coping: Asymmetry of dopamine efferents within the prefrontal cortex (Craig W. Berridge, Rodrigo A. Espafia and Thomas A. Stalnaker). 4. The nature and determinants of handedness (Alan A, Beaton). II. Neuroimaging and brain stimulation studies. 5. Characterizing functional asymmetries with brain mapping (Karl J. Friston). 6. Anatomical brain asymmetries and their relevance for functional asymmetries (Lutz JLncke and Helmuth Steinmetz). 7. Transcranial magnetic stimulation studies of asymmetry of cognitive functions in the brain (Alvaro Pascual-Leone and Vincent Walsh). III. Visual laterality. 8. Interaction between the hemispheres and its implications for the processing capacity of the brain (Marie T. Banich). 9. Asymmetries in encoding spatial relations (Bruno Laeng, Christopher F.
BOOK
REPORTS
'.
981
Chabris and Stephen M. Kosslyn). 10. Complexities of interhemispheric communication in sensoimotor tasks r~+ vealed by high-density event-related potential mapping (Clifford D. Saron, John J. Foxe, Char’lbs E. Schroeder and Herber G. Vaughan, Jr.). IV. Auditory laterality. 11. Hemispheric asymmetries in the processing of tonal stimuli (Robert J. Zatorre). 12. Dichotic listening in the study of auditory laterality (Kenneth Hugdahl).’ 13. Effects of attention on hemispheric asymmetry (Daniel S. O’Leary). V. Emotional laterality. 14. The functional neuroimaging of human emotion: Asymmetric contributions of cortical and subcortical circuitryt(Diego Pizaagalli, Alexander J. Schakman and Richard J. Davidson). 15. Regional brain activity in anxiety and depression, cognition/emotion interaction, and emotion regulation (Wendy Heller, Nancy S. Koven and Gregory A. Miller). 16. The state and trait nature of frontal EEG ssyeet,v in emotion (James A. Coan and John J.B. Allen). VI. Neurological disorders. 17. Agenesis of the corpus callosum (Maryse Lassonde and Hannelore C. Sauerwein). 18. Developmental disorders: Dyslexia (Mark A. Eckert and Christiana M. Leonard). 19. Structural correlates of brain asymmetry: Studies in left-handed and dyslexic individuals (Michel Habib and Fabrice Robichon). VII. Psychiatric disorders. 20. Frontal and parietotemporal asymmetries in depressive disorders: Behavioral, electrophysiologic, and neuroimaging findings (Gerard E. Bruder). 21. The laterality of schizophrenia (Michael F. Green, Mark J. Sergi and Robert S. Kern). Cbntributors. Author index. Subject index. Learnina and Genemlisation: With Applications to Neural Networks. By M. Vidyasagar. Springer-Verlag, London. (2003). 488 pages. $119.00, EUR 99.95, SFR 166.00, GBP 60.00. Contents: Preface to the second edition. Preface to the first edition. 1. Introduction. 2. Preliminaries. 3. Problem formulations. 4. Vapnik-Chervonenkis, pseudoand fat-shattering dimensions. 5. Uniform convergence of empirical means. 6. Learning under a fixed probability measure. 7. Distribution-free learning. 8. Learning under an intermediate family of probabilities. 9. Alternate models of learning. 10. Applications to neural networks. 11. Applications to control systems. 12. Some open problems. Handbook of Data Minina and Knowledae Discovery. Edited by Willi Klasgen and Jan M. iytkow. Oxford University Press, New York. (2002). 1026 pages. $250.00. Contents: Foreword: Enhancing the intelligence of discovery systems (Herbert A. Simon). Foreword: Data mining coming of age (Gregory Piatetsky-Shapiro). Preface (Willi KlBsgen and Jan M. iytkow). Part I. Data mining and knowledge discovery. 1. Knowledge discovery in databases: The purpose, necessity, and challenges (Willi Kkisgen and Jan M. iytkow). 2. The knowledge discovery process (Willi Klijsgen and Jan M. iytkow). 3. Multidisciplinary contributions to knowledge discovery (Jan M. iytkow and Willi KBsgen). Part II. Fundamental concepts. 4. Types and forms of data (Willi Kliisgen). 5. Types and forms of knowledge (patterns). 5.1. Contingency tables (Jan M. iytkow). 5.2. Subgroup patterns (Willi KlBsgen). 5.3. Rules (Jan M. iytkow). 5.4. Decision trees (Jan M. iytkow). 5.5. Functional relations (Jan M. iytkow). 5.6. Clusters (Padhraic Smyth). 5.7. Taxonomies and concept hierarchies (Jan M. iytkow). 5.8. Probabilistic and causal networks (Clark Glymour). 5.9. Neural networks (Witold Pedrycz). 6. Data and knowledge in database systems. 6.1. Relational databases (Raghu Ramakrishnan). 6.2. Object-oriented databases (Klaus R. Dittrich and Anca Vaduva). 6.3. Multidimensional databases and online analytical processing (Surajit Chaudhuri and Umesh Dayal). 6.4. Deductive databases (Carlo Zaniolo). 6.5. Parallel databases (Shahram Ghandeharizadeh and Frank Sommers). 6.6. Distributed, heterogeneous, and federated databases (Witold Litwin). 6.7. Meta-data management (Klaus R. Dittrich and Anca Vaduva). 7. Logic perspective on data and knowledge (Lech Polkowski and Andrzej Skowron). 8. Statistics perspective on data and knowledge (David Madigan and Martha Nsson). 9. Rough sets perspective on data and knowledge (Andrzej Skowron, Jan Komorowski, Zdisislaw Pawlak and Lech Polkowski). 10. Fuzzy sets perspective on data and knowledge (Witold Pedrycz). 11. Search techniques (Weixiong Zhang). 12. Stages of the discovery process (Thomas Part III. The process of knowledge discovery in databases. Reinartz). 13. Data warehousing. 13.1. Data cleaning and loading (Tqby Bloom). 13.2. Warehouse administration (Wolfgang Lehner). 14. Data reduction. 14.1. Sampling (David Madigan and Martha Nason). 14.2. Feature selection (Hiroshi Motoda and Huan Liu). 14.3. Feature aggregation (Hiroshi Motoda and Huan Liu). 14.4. Discretization of numerical attributes (Jerzy W. Grzymala-Busse). 15. Data visualization for domain exploration. 15.1. Interactive statistical graphics (Graham J. Wills and Daniel Keim). 15.2. Highly multivariate interaction techniques (Martin Theus). 15.3. Geographical information systems (Martin Theus). 15.4. Animation techniques (Stephen G. Eick). 16. Data mining tasks and methods. 16.1. Classification. 16.1.1. The goal of classification (Hans-Hermann.Bock). 16.1.2. Classification methodology (Hans-Hermann Bock). 16.1.3. Decision-tree discovery (Ronny Kohavi and J. Ross Quinlan). 16.1.4. Decision rules (Willi KlGsgen). 16.1.5. Bayesian classification (Nir Friedman and Ronny Kohavi) 16.1.6. Nearest-neighbor approaches (Belur V. Dasarathy). 16.1.7. Regression (Robert Henery). 16.1.8. Neural network approaches (Andreas Niirnberger, Witold Pedrycz and Rudolf Kruse). 16.1.9. Multicriteria classification (Salvatore Greco, Benedetto Matarazzo and Roman Slowinski). 16.2. Rule discovery. 16.2.1. Rough set approaches for discovering rules and attribute dependencies (qojciech Ziarko). 16.2.2. Characteristic rules (Jiawei Han). 16.2.3. Association rules (Heikki Mannila). 16.2.4. Inductive logic programming approaches (S&o Dieroski). 16.3. Subgroup discovery. 16.3.1. Deviation analysis (Willi Kkisgen). 16.3.2. Change analysis (Willi KlGsgen). 16.3.3. Drill-down methods (Tejwansh S. Anand). 16.4. Equation fitting. 16.4.1. Methodology for equation fitting (Takashi Wsshio and Hiroshi Motoda). 16.4.2. Equation finders (Jan M.