Classification clustering knowledge discovery (31 resultados)

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Taschenbuch. Condición: Neu. Classification and Clustering for Knowledge Discovery | Saman K. Halgamuge (u. a.) | Taschenbuch | Studies in Computational Intelligence | xii | Englisch | 2010 | Springer | EAN 9783642065422 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. 'Classification and Clustering for Knowledge Discovery' also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications. …

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Condición: New. Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in.

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Condición: New. pp. 374.

Buch. Condición: Neu. Neuware - Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. 'Classification and Clustering for Knowledge Discovery' also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Large amount of data have been collected routinely in the course of day-to-day work in different fields. Typically, the datasets constantly grow accumulating a large number of features, which are not equally important in decision-making. Rough set theory (RST)recently becomes very popular in dimensionality reduction and feature selection of large datasets. The RST approach to feature selection is used to determine a subset of features (or attributes) called reduct which can predict the decision concepts. In reality, there are multiple reducts in a given information system used for developing classifiers, amongst which the best performer is chosen as the final solution to the problem. Selecting a reduct with good performance is time expensive, as there might be many reducts of a given dataset. Therefore, obtaining a best performer classifier is not practical rather ensemble of different classifiers may lead to better classification accuracy. However, combining large number of classifiers increases complexity of the system. The work trades off between these two approaches and creates an efficient ensemble classifier.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. 'Classification and Clustering for Knowledge Discovery' also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications. 368 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. 'Classification and Clustering for Knowledge Discovery' also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 368 pp. Englisch.…

Condición: New. Print on Demand pp. 370 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

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Condición: New. PRINT ON DEMAND pp. 370.