Inductive Classifier Learning From Data
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Inductive Classifier Learning From Data
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Author : Yong Ma
language : en
Publisher:
Release Date : 1995
Inductive Classifier Learning From Data written by Yong Ma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Artificial intelligence categories.
Abstract: "A central problem in artificial intelligence is reasoning under uncertainty. This thesis views inductive learning as reasoning under uncertainty and develops an Extended Bayesian Belief Function approach that allows a two-layer representation of the probabilistic rules: basic probabilistic belief and their confidences, which are independent of each other and represent different semantics of the rules. The use of the confidence measure of probabilistic rules can thus handle many difficult problems in inductive learning, including noise, missing values, small samples, inter-attribute dependency, and irrelevant or partially relevant attributes, all of which are characteristics of real- world induction tasks. The theoretical framework is based upon an uncertainty calculus, Dempster-Shafer theory which allows an explicit representation of complete or partial lack of knowledge. This explicit representation is used to quantify and discount the effects of unreliable probability estimates due to noise and small samples, and to account for inter-attribute dependency and irrelevant or partially relevant attributes. Based on this methodology, a learning system, called IUR (Induction of Uncertain Rules) that uses only the first-order correlation information, is developed and experimentally demonstrated to outperform the major existing induction systems on many of the standard test sets. Future research includes extending IUR to use higher-order correlation information and integrating the Extended Bayesian Belief Function approach to other learning paradigms such as decision trees and neural networks."
Data Science Classification And Related Methods
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Author : Chikio Hayashi
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Data Science Classification And Related Methods written by Chikio Hayashi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.
This volume contains selected papers covering a wide range of topics, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. The result is a broad view of the state of the art, making this an essential work not only for data analysts, mathematicians, and statisticians, but also for researchers involved in data processing at all stages from data gathering to decision making.
Databases And Information Systems Vi
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Author : Marite Kirikova
language : en
Publisher: IOS Press
Release Date : 2011
Databases And Information Systems Vi written by Marite Kirikova and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
Selected Papers from the Ninth International. This volume presents papers from the Ninth International Baltic Conference on Databases and Information Systems Baltic DBIS 2010 which took place in Riga, Latvia in July 2010. Since this successful biennial series began in 1994, the Baltic DBIS confer
Progress In Discovery Science
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Author : Setsuo Arikawa
language : en
Publisher: Springer
Release Date : 2003-07-31
Progress In Discovery Science written by Setsuo Arikawa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-31 with Computers categories.
Annotation This book documents the scientific outcome and constitutes the final report of the Japanese research project on discovery science. During three years more than 60 scientists participated in the project and developed a wealth of new methods for knowledge discovery and data mining. The 52 revised full papers presented were carefully reviewed and span the whole range of knowledge discovery from logical foundations and inductive reasoning to statistical inference and computational learning. A broad variety of advanced applications are presented including knowledge discovery and data mining in very large databases, knowledge discovery in network environments, text mining, information extraction, rule mining, Web mining, image processing, and pattern recognition.
Bridging The Gap Between Machine Learning And Affective Computing
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Author : Zhen Cui
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-05
Bridging The Gap Between Machine Learning And Affective Computing written by Zhen Cui and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-05 with Science categories.
Affective computing refers to computing that relates to, arises from, or influences emotions, as pioneered by Rosalind Picard in 1995. The goal of affective computing is to bridge the gap between human and machines and ultimately enable robots to communicate with human naturally and emotionally. Recently, the research on affective computing has gained considerable progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing mainly focuses on estimating of human emotions through different forms of signals, e.g., face video, EEG, Speech, PET scans or fMRI. Inferring the emotion of humans is difficult, as emotion is a subjective, unconscious experience characterized primarily by psycho-physiological expressions and biological reactions. It is influenced by hormones and neurotransmitters such as dopamine, noradrenaline, serotonin, oxytocin, GABA… etc. The physiology of emotion is closely linked to arousal of the nervous system with various states and strengths relating, apparently, to different particular emotions. To understand “emotion” or “affect” merely by machine learning or big data analysis is not enough, but the understanding and applications from the intrinsic features of emotions from the neuroscience aspect is essential.
Fuzzy Sets And Systems Ii
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Author : Edy Portmann
language : en
Publisher: Springer Nature
Release Date : 2026-01-02
Fuzzy Sets And Systems Ii written by Edy Portmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-02 with Business & Economics categories.
As organizations strive to balance innovation with accountability, this second volume in a trilogy on fuzzy systems and digital ethics examines how ethical and sustainable practices can be operationalized at the institutional level. Through the lens of design science and fuzzy logic, it demonstrates how organizations can build resilient, data-driven infrastructures that support responsible decision-making. Theoretical models and empirical insights highlight the role of fuzzy logic in enhancing the adaptability and integrity of enterprise systems. Volume II extends the ethical framework of the honorable merchant to the organizational level. It examines how institutions can uphold ethical standards in competitive environments, with case studies from business informatics, computer science, and engineering. Topics include performance management, customer classification, employee satisfaction, marketing analytics, and service level optimization. The volume concludes with a responsible actions framework, reinforcing the integration of ethics into complex organizational processes. This textbook trilogy is primarily intended for students of computer science, business information systems, and innovation management who aspire to make a meaningful impact. It will also appeal to managers who value balanced perspectives and data-driven analysis.
Discovery Science
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Author : Setsuo Arikawa
language : en
Publisher: Springer
Release Date : 2003-07-31
Discovery Science written by Setsuo Arikawa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-31 with Science categories.
This book constitutes the refereed proceedings of the First International Conference on Discovery Science, DS'98, held in Fukuoka, Japan, in December 1998. The volume presents 28 revised full papers selected from a total of 76 submissions. Also included are five invited contributions and 34 selected poster presentations. The ultimate goal of DS'98 and this volume is to establish discovery science as a new field of research and development. The papers presented relate discovery science to areas as formal logic, knowledge processing, machine learning, automated deduction, searching, neural networks, database management, information retrieval, intelligent network agents, visualization, knowledge discovery, data mining, information extraction, etc.
Advances In Feature Selection For Data And Pattern Recognition
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Author : Urszula Stańczyk
language : en
Publisher: Springer
Release Date : 2017-11-16
Advances In Feature Selection For Data And Pattern Recognition written by Urszula Stańczyk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-16 with Technology & Engineering categories.
This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.
Healthcare And Big Data Management
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Author : Bairong Shen
language : en
Publisher: Springer
Release Date : 2017-10-20
Healthcare And Big Data Management written by Bairong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-20 with Science categories.
The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.
Artificial Intelligence In Real Time Control 1994 Airtc 94
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Author : Alfons Crespo
language : en
Publisher: Pergamon
Release Date : 1995
Artificial Intelligence In Real Time Control 1994 Airtc 94 written by Alfons Crespo and has been published by Pergamon this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
Paperback. Artificial Intelligence is one of the new technologies that has contributed to the successful development and implementation of powerful and friendly control systems. These systems are more attractive to end-users shortening the gap between control theory applications. The IFAC Symposia on Artificial Intelligence in Real Time Control provides the forum to exchange ideas and results among the leading researchers and practitioners in the field. This publication brings together the papers presented at the latest in the series and provides a key evaluation of present and future developments of Artificial Intelligence in Real Time Control system technologies.