9781611976267 - mining imperfect data: with examples in r and python (mathematics in industry) de pearson, ronald k. (13 resultados)
Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 90,53
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Condición: new.
Idioma: Inglés
Editorial: Society for Industrial & Applied Mathematics,U.S., New York, 2020
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 108,06
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Paperback. Condición: new. Paperback. It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropriate t…reatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them.As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python.Mining Imperfect Data: With Examples in R and Python, Second Editionpresents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage);includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them; andprovides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities. Focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 96,85
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Idioma: Inglés
Editorial: Society for Industrial and Applied Mathematics,U.S., US, 2020
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 120,29
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Paperback. Condición: New. Second Edition. It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropri…ate treatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them.As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python.Mining Imperfect Data: With Examples in R and Python, Second Editionpresents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage);includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them; andprovides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities.
Idioma: Inglés
Editorial: MP-SIA SIAM - Society for Industrial and Applied M, 2020
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 111,31
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Editorial: Society For Industrial & Applied Mathematics,U.S., 2020
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 102,93
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Paperback / Softback. Condición: Brand New. 2nd revised edition edition. 481 pages. 10.08x7.01x1.26 inches. In Stock.
Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 115,66
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Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 127,92
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Condición: New. 2nd edition NO-PA16APR2015-KAP.
Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
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EUR 123,73
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Condición: New.
Idioma: Inglés
Editorial: Society for Industrial & Applied Mathematics,U.S., 2020
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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
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EUR 110,51
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Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Editorial: SIAM - Society for Industrial and Applied Mathematics, 2020
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 133,57
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Condición: New. In English.
Idioma: Inglés
Editorial: Society for Industrial and Applied Mathematics,U.S., US, 2020
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 117,19
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Paperback. Condición: New. Second Edition. It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropri…ate treatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them.As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python.Mining Imperfect Data: With Examples in R and Python, Second Editionpresents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage);includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them; andprovides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities.
Idioma: Inglés
Editorial: Society for Industrial & Applied Mathematics,U.S., New York, 2020
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 175,56
Envío por EUR 31,95Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropriate t…reatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them.As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python.Mining Imperfect Data: With Examples in R and Python, Second Editionpresents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage);includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them; andprovides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities. Focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
