9780470222805 - Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications de Myatt, Glenn J. (30 resultados)

paperback. Condición: Good. Paperback--exlibrary--otherwise excellent condition.

Condición: acceptable. Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may be missing bundled media.

paperback. Condición: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condición: Good. paperback. Former Library book. Wrappers are firm, text block clean, without highlights/underlining or markings. Some rubbing/curling to wrappers. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.

Softcover. 291 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. w15855 9780470222805 Sprache: Englisch Gewicht in Gramm: 350.

Condición: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

paperback. Condición: Like New. 1st Edition. Ships in a BOX from Central Missouri! Like Brand NEW. No tears, highlighting or writing because it's never been used! May have minor shelf wear. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

paperback. Condición: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condición: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: new.

Condición: New.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: new. Paperback. A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naive Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader's ability to find patterns in data will be greatly enhanced due to the book's combination of statistical learning with powerful visualization techniques. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New.

Condición: New. In.

PF. Condición: New.

Condición: New. pp. 308 Illus.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader's ability to find patterns in data will be greatly enhanced due to the book's combination of statistical learning with powerful visualization techniques. Num Pages: 308 pages, Illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 233 x 158 x 17. Weight in Grams: 418. . 2009. 1st Edition. paperback. . . . .

Condición: As New. Unread book in perfect condition.

Paperback. Condición: Brand New. 1st edition. 291 pages. 9.10x6.10x0.60 inches. In Stock.

Condición: New. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader's ability to find patterns in data will be greatly enhanced due to the book's combination of statistical learning with powerful visualization techniques. Num Pages: 308 pages, Illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 233 x 158 x 17. Weight in Grams: 418. . 2009. 1st Edition. paperback. . . . . Books ship from the US and Ireland.

Condición: New. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader s ability to find patterns in data will be greatly enhanced due to the book s combination of statistical learn.

Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condición: new. Paperback. A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naive Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader's ability to find patterns in data will be greatly enhanced due to the book's combination of statistical learning with powerful visualization techniques. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. Neuware - A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques.

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Paperback. Condición: Brand New. 1st edition. 291 pages. 9.10x6.10x0.60 inches. In Stock. This item is printed on demand.

Paperback. Condición: new. Paperback. A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naive Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization. This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader's ability to find patterns in data will be greatly enhanced due to the book's combination of statistical learning with powerful visualization techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.