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In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. 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,650grams, ISBN:9780470846797.
Aug 22, 2003. Zustand: gebraucht; wie neu. (507-3).
Zustand: New.
Zustand: New.
Zustand: As New. Unread book in perfect condition.
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In den WarenkorbZustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 98,17
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In den WarenkorbZustand: As New. Unread book in perfect condition.
Sprache: Englisch
Verlag: John Wiley & Sons 08.2003., 2003
ISBN 10: 047084678X ISBN 13: 9780470846780
Anbieter: Vulkaneifel Bücher, Birgel, Deutschland
hardcover. Zustand: Wie neu. Auflage: 1. minimale Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 680.
Anbieter: Antiquariat Bookfarm, Löbnitz, Deutschland
Softcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 GIU 9780470846780 Sprache: Englisch Gewicht in Gramm: 1150.
Taschenbuch. Zustand: Neu. Applied Statistical Techniques for Data Mining | Darshana Pandya (u. a.) | Taschenbuch | Englisch | 2022 | Scholars' Press | EAN 9786202319034 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Data cleansing is a critical step for data preparation. The values lost in the database are a common problem faced by data analysts. Missing values in data mining is continual troubles that can grounds errors in data analysis. Randomly missing elements in the attribute/dataset make data analysis complicated and also confused to consolidated result. It affects the accuracy of the result and intermediate queries. By using statistical / numerical methods, one can recover the missing data and decrease the suspiciousness in the database. The present research gives an applied approach of Newton Forward Interpolation (NFI) method to recover the missing values and other different methods also.Data in the dataset is always remaining as the basic building blocks for any query and further task and decisions. If basis data is incomplete or dataset have missing values the none cannot assume about well up to date final reports. In data mining missing values recognition and recovery is still major issue with irregular data. To overcome from such situation there is need of statistical or numerical techniques to recover the missing values in the dataset.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 232 pp. Englisch.
Anbieter: Mispah books, Redhill, SURRE, Vereinigtes Königreich
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In den Warenkorbhardcover. Zustand: Very Good. Very Good. Dust Jacket may NOT BE INCLUDED.CDs may be missing. SHIPS FROM MULTIPLE LOCATIONS. book.
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In den WarenkorbHRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data cleansing is a critical step for data preparation. The values lost in the database are a common problem faced by data analysts. Missing values in data mining is continual troubles that can grounds errors in data analysis. Randomly missing elements in the attribute/dataset make data analysis complicated and also confused to consolidated result. It affects the accuracy of the result and intermediate queries. By using statistical / numerical methods, one can recover the missing data and decrease the suspiciousness in the database. The present research gives an applied approach of Newton Forward Interpolation (NFI) method to recover the missing values and other different methods also.Data in the dataset is always remaining as the basic building blocks for any query and further task and decisions. If basis data is incomplete or dataset have missing values the none cannot assume about well up to date final reports. In data mining missing values recognition and recovery is still major issue with irregular data. To overcome from such situation there is need of statistical or numerical techniques to recover the missing values in the dataset. 232 pp. Englisch.
Anbieter: moluna, Greven, Deutschland
EUR 78,26
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Data cleansing is a critical step for data preparation. The values lost in the database are a common problem faced by data analysts. Missing values in data mining is continual troubles that can grounds errors in data analysis. Randomly missing elements in t.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 130,84
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In den WarenkorbZustand: New. Print on Demand.
Anbieter: Books Puddle, New York, NY, USA
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Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data cleansing is a critical step for data preparation. The values lost in the database are a common problem faced by data analysts. Missing values in data mining is continual troubles that can grounds errors in data analysis. Randomly missing elements in the attribute/dataset make data analysis complicated and also confused to consolidated result. It affects the accuracy of the result and intermediate queries. By using statistical / numerical methods, one can recover the missing data and decrease the suspiciousness in the database. The present research gives an applied approach of Newton Forward Interpolation (NFI) method to recover the missing values and other different methods also.Data in the dataset is always remaining as the basic building blocks for any query and further task and decisions. If basis data is incomplete or dataset have missing values the none cannot assume about well up to date final reports. In data mining missing values recognition and recovery is still major issue with irregular data. To overcome from such situation there is need of statistical or numerical techniques to recover the missing values in the dataset.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This reprint comprises a compilation of 15 insightful research papers published in the Special Issue 'Applied Statistical Modeling and Data Mining' within the Mathematics journal. Spanning multiple domains at the intersection of statistics, machine learning, and real-world applications, the collection presents diverse perspectives and innovative approaches in the field of applied statistical modeling and data mining. These selected papers explore diverse and important topics, including predictive modeling in healthcare, cybersecurity in transportation systems, data quality assessment, emergency call modeling, and innovative crime prevention strategies, among others. By covering a wide spectrum of subjects, this reprint serves as a valuable resource for researchers, academics, and practitioners interested in addressing contemporary challenges across diverse domains through statistical modeling, data mining, and machine learning applications.
Anbieter: preigu, Osnabrück, Deutschland
Buch. Zustand: Neu. Applied Statistical Modeling and Data Mining | Buch | Englisch | 2024 | MDPI AG | EAN 9783725811052 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.