Modeling Techniques in Predictive Analytics: Business Problems and Solutions With R

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9780133412932: Modeling Techniques in Predictive Analytics: Business Problems and Solutions With R

Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller's unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you've identified it, and then how to successfully model that data. You'll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today's #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it's easy to find for those who want it (and easy to skip for those who don't).

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Miller, Thomas W.
Editore: Pearson FT Press (2013)
ISBN 10: 0133412938 ISBN 13: 9780133412932
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Descrizione libro Pearson FT Press, 2013. Condizione libro: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller's unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you've identified it, and then how to successfully model that data. You'll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today's #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it's easy to find for those who want it (and easy to skip for those who don't). Codice libro della libreria ABE_book_new_0133412938

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Miller, Thomas W.
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Descrizione libro Pearson Education (US), United States, 2013. Hardback. Condizione libro: New. 238 x 186 mm. Language: English . Brand New Book. Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you ve identified it, and then how to successfully model that data. You ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it s easy to find for those who want it (and easy to skip for those who don t). Codice libro della libreria AAK9780133412932

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Miller, Thomas W.
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Descrizione libro Pearson FT Press, 2013. Hardcover. Condizione libro: New. book. Codice libro della libreria 0133412938

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Descrizione libro Ft Pr, 2013. Hardcover. Condizione libro: Brand New. 1st edition. 352 pages. 9.55x7.37x0.93 inches. In Stock. Codice libro della libreria zk0133412938

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Miller, Thomas W.
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Descrizione libro Pearson Education (US), United States, 2013. Hardback. Condizione libro: New. 238 x 186 mm. Language: English . Brand New Book. Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you ve identified it, and then how to successfully model that data. You ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it s easy to find for those who want it (and easy to skip for those who don t). Codice libro della libreria AAK9780133412932

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Descrizione libro Pearson FT Press. Hardcover. Condizione libro: New. 0133412938 BRAND NEW W/FAST SHIPPING! This item is: Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R, 1st Ed., 2014, by Miller, Thomas W.; FORMAT: Hardcover; ISBN: 9780133412932. Choose Expedited for fastest shipping! Our 98%+ rating proves our commitment! We cannot ship to PO Boxes/APO address. To avoid ordering the wrong item, please check your item's ISBN number!. Codice libro della libreria P9780133412932

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