Pattern recognition data analysis (95 risultati)

Trade Paperback. Condizione: Near Fine. Condizione sovraccoperta: no jacket (as issued). *Excellent* Square, clean, and bright. No marks! A little wear to the exterior. I ship daily. 117 pp. Appendices. Bibliography.

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Paperback. Condizione: Brand New. 2015 edition. 100 pages. 9.30x6.20x0.23 inches. In Stock.

Condizione: New. pp. 173 1st ed. 2018 edition NO-PA16APR2015-KAP.

Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Condizione: New. pp. 280.

Condizione: New. pp. 280.

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Condizione: New. pp. 280.

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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Condizione: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condizione: New. pp. 256.

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Taschenbuch. Condizione: Neu. Learning Structured Data for Human Action Analysis | A unified approach for visual pattern recognition | Tuan Hue Thi | Taschenbuch | 228 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846548332 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Condizione: New. In English.

hardcover. Condizione: Gut. 253 Seiten; 9783319034096.3 Gewicht in Gramm: 500.

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Condizione: New. pp. 238.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.…

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.…

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.…

Taschenbuch. Condizione: Neu. Data Analysis and Pattern Recognition in Multiple Databases | Animesh Adhikari (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xv | Englisch | 2016 | Springer | EAN 9783319377278 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Paperback. Condizione: Brand New. 228 pages. 8.66x5.91x0.52 inches. In Stock.

Hardcover. Condizione: Brand New. 2014 edition. 245 pages. 9.75x6.75x0.75 inches. In Stock.

Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, and may have sticker on cover, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Paperback. Condizione: Brand New. reprint edition. 256 pages. 9.25x6.10x0.58 inches. In Stock.