classification clustering (533 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware -In supervised classification of remotely sensed imagery the analysts require a plenty of time for generating the representative signatures of the possible land-cover classes present in the image. Although the notion of picking a large number of input signatures leads to more efficient results but in most of the situations the time is an important factor. To save the lavish time, besides to obtain the reliable results, is the requirement of most of the analysts. In this study the results of supervised classification are used as reference for checking the reliability of the results obtained with guided clustering technique as this technique is based on ground truth data and the ancillary information.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.

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Frankfurt, Peter Lang 2010. 195 S., OPappband. gering bestoßen, sonst neuwertig.

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Sprache: Englisch OriginalKarton. Noch eingeschweißtes Exemplar!

Taschenbuch. Zustand: Neu. KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis | Harikumar Rajaguru (u. a.) | Taschenbuch | 56 S. | Englisch | 2017 | Anchor Academic Publishing | EAN 9783960671404 | Verantwortliche Person für die EU: Anchor Academic Publishing, Herrmannsthal 119k, 22119 Hamburg, kontakt[at]bedey-media[dot]de | Anbieter: preigu.

Zustand: Good. Volume 1. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9783642231650.

Zustand: Gut. Zustand: Gut | Seiten: 108 | Sprache: Englisch | Produktart: Bücher.

Taschenbuch. Zustand: Neu. Neuware -This research work focused on the satellite image clustering by developing some numerical algorithms to analyze the satellite images captured by satellites. it is aimed to enhance the classification accuracy by two proposed algorithms. Each approach goes through three phrases i.e preprocessing, segmentation and classification. these approaches show optimal results under observing condition, dynamic variation in regional details or noise effect degrades its performance.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This research book focused on the satellite image clustering by developing numerical algorithm to analyse the satellite images captured by satellites. In this book it is aimed to enhance the classification accuracy. In this research work, three algorithms were proposed. Each approach goes through three phrases i.e preprocessing, segmentation and classification. Clustering algorithms are used at segmentation stage. The proposed clustering algorithms is Moving KFCM algorithm. Feed forward neural network classifier is used at classification stage. After a study of several test images it is shown that Moving KFCM algorithm is working well for finding all regions like trees, shades, buildings and roads.Books on Demand GmbH, Überseering 33, 22297 Hamburg 92 pp. Englisch.

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Taschenbuch. Zustand: Neu. Neuware -I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - As we enter the third decade of the World Wide Web (WWW), the textual revolution has seen a tremendous change in the availability of online information. Finding inf- mation for just about any need has never been more automatic-just a keystroke or mouseclick away. While the digitalization and creation of textual materials continues at light speed, the ability to navigate, mine, or casually browse through documents too numerous to read (or print) lags far behind. What approaches to text mining are available to ef ciently organize, classify, label, and extract relevant information for today's information-centric users What algorithms and software should be used to detect emerging trends from both text streamsandarchives Thesearejustafewoftheimportantquestionsaddressedatthe Text Mining Workshop held on April 28, 2007, in Minneapolis, MN. This workshop, the fth in a series of annual workshops on text mining, was held on the nal day of the Seventh SIAM International Conference on Data Mining (April 26-28, 2007). With close to 60 applied mathematicians and computer scientists representing universities, industrial corporations, and government laboratories, the workshop f- tured both invited and contributed talks on important topics such as the application of techniques of machine learning in conjunction with natural language processing, - formation extraction and algebraic/mathematical approaches to computational inf- mation retrieval. The workshop's program also included an Anomaly Detection/Text Mining competition. NASA Ames Research Center of Moffett Field, CA, and SAS Institute Inc. of Cary, NC, sponsored the workshop.

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