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 quantitat...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Upper Saddle River, N.J.
Pearson Education
2013, ©2014
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9780133412963/?ar |
| Zusammenfassung: | 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). |
| Beschreibung: | Includes bibliographical references and index. - Print version record |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 9780133412963 0133412962 0133412938 9780133412932 |
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| spelling | Miller, Thomas W. 1946- VerfasserIn aut Modeling techniques in predictive analytics business problems and solutions with R Thomas W. Miller Business problems and solutions with R Upper Saddle River, N.J. Pearson Education 2013, ©2014 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Print version record 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). Business forecasting Mathematical models Business forecasting Data processing R (Computer program language) Prévision commerciale ; Modèles mathématiques Prévision commerciale ; Informatique R (Langage de programmation) Business forecasting ; Data processing Business forecasting ; Mathematical models 9780133412932 Erscheint auch als Druck-Ausgabe 9780133412932 |
| spellingShingle | Miller, Thomas W. 1946- Modeling techniques in predictive analytics business problems and solutions with R Business forecasting Mathematical models Business forecasting Data processing R (Computer program language) Prévision commerciale ; Modèles mathématiques Prévision commerciale ; Informatique R (Langage de programmation) Business forecasting ; Data processing Business forecasting ; Mathematical models |
| title | Modeling techniques in predictive analytics business problems and solutions with R |
| title_alt | Business problems and solutions with R |
| title_auth | Modeling techniques in predictive analytics business problems and solutions with R |
| title_exact_search | Modeling techniques in predictive analytics business problems and solutions with R |
| title_full | Modeling techniques in predictive analytics business problems and solutions with R Thomas W. Miller |
| title_fullStr | Modeling techniques in predictive analytics business problems and solutions with R Thomas W. Miller |
| title_full_unstemmed | Modeling techniques in predictive analytics business problems and solutions with R Thomas W. Miller |
| title_short | Modeling techniques in predictive analytics |
| title_sort | modeling techniques in predictive analytics business problems and solutions with r |
| title_sub | business problems and solutions with R |
| topic | Business forecasting Mathematical models Business forecasting Data processing R (Computer program language) Prévision commerciale ; Modèles mathématiques Prévision commerciale ; Informatique R (Langage de programmation) Business forecasting ; Data processing Business forecasting ; Mathematical models |
| topic_facet | Business forecasting Mathematical models Business forecasting Data processing R (Computer program language) Prévision commerciale ; Modèles mathématiques Prévision commerciale ; Informatique R (Langage de programmation) Business forecasting ; Data processing Business forecasting ; Mathematical models |
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