applied data mining statistical (19 resultados)

Paperback. Condición: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.25.

Condición: acceptable. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Acceptable condition! Any other included accessories are also in Acceptable condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear such as cover tears discoloration, staining, marks, scuffs, etc. All pages intact.

Condición: 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.

Condición: gebraucht; wie neu. (507-3).

Condición: New.

Condición: New. In.

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.

hardcover. Condición: Wie neu. Auflage: 1. minimale Lagerspuren am Buch, Inhalt einwandfrei und ungelesen 223866 Sprache: Englisch Gewicht in Gramm: 680.

Hardcover. Condición: new. Hardcover. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condición: New.

Taschenbuch. Condición: 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.

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: 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.

Condición: 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.

Taschenbuch. Condición: 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.

Condición: New. Print on Demand.

Buch. Condición: 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.

Condición: New. PRINT ON DEMAND.