Statistical and machine-learning data mining : techniques for better predictive modeling and analysis of big data / / Bruce Ratner |
Autore | Ratner Bruce |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Boca Raton : , : Taylor & Francis, , 2012 |
Descrizione fisica | 1 online resource (524 p.) |
Disciplina | 658.8/72 |
Altri autori (Persone) | RatnerBruce |
Soggetto topico |
Database marketing - Statistical methods
Data mining - Statistical methods |
ISBN |
0-429-24862-8
1-4665-5121-6 1-280-12244-7 9786613526304 1-4398-6092-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Dedication; Contents; Preface; Acknowledgments; About the Author; 1. Introduction; 2. Two Basic Data Mining Methods for Variable Assessment; 3. CHAID-Based Data Mining for Paired-Variable Assessment; 4. The Importance of Straight Data: Simplicity and Desirability for Good Model-Building Practice; 5. Symmetrizing Ranked Data: A Statistical Data Mining Method for Improving the Predictive Power of Data; 6. Principal Component Analysis: A Statistical Data Mining Method for Many-Variable Assessment; 7. The Correlation Coefficient: Its Values Range between Plus/Minus 1, or Do They?
8. Logistic Regression: The Workhorse of Response Modeling9. Ordinary Regression: The Workhorse of Profit Modeling; 10. Variable Selection Methods in Regression: Ignorable Problem, Notable Solution; 11. CHAID for Interpreting a Logistic Regression Model; 12. The Importance of the Regression Coefficient; 13. The Average Correlation: A Statistical Data Mining Measure for Assessment of Competing Predictive Models and the Importance of the Predictor Variables; 14. CHAID for Specifying a Model with Interaction Variables; 15. Market Segmentation Classification Modeling with Logistic Regression 16. CHAID as a Method for Filling in Missing Values17. Identifying Your Best Customers: Descriptive, Predictive, and Look-Alike Profiling; 18. Assessment of Marketing Models; 19. Bootstrapping in Marketing: A New Approach for Validating Models; 20. Validating the Logistic Regression Model: Try Bootstrappin; 21. Visualization of Marketing ModelsData Mining to Uncover Innards of a Model; 22. The Predictive Contribution Coefficient: A Measure of Predictive Importance; 23. Regression Modeling Involves Art, Science, and Poetry, Too; 24. Genetic and Statistic Regression Models: A Comparison 25. Data Reuse: A Powerful Data Mining Effect of the GenIQ Model26. A Data Mining Method for Moderating Outliers Instead of Discarding Them; 27. Overfitting: Old Problem, New Solution; 28. The Importance of Straight Data: Revisited; 29. The GenIQ Model: Its Definition and an Application; 30. Finding the Best Variables for Marketing Models; 31. Interpretation of Coefficient-Free Models |
Record Nr. | UNINA-9910778813003321 |
Ratner Bruce
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Boca Raton : , : Taylor & Francis, , 2012 | ||
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Lo trovi qui: Univ. Federico II | ||
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Statistical and machine-learning data mining : techniques for better predictive modeling and analysis of big data / / Bruce Ratner |
Autore | Ratner Bruce |
Edizione | [2nd ed.] |
Pubbl/distr/stampa | Boca Raton : , : Taylor & Francis, , 2012 |
Descrizione fisica | 1 online resource (524 p.) |
Disciplina | 658.8/72 |
Altri autori (Persone) | RatnerBruce |
Soggetto topico |
Database marketing - Statistical methods
Data mining - Statistical methods |
ISBN |
0-429-24862-8
1-4665-5121-6 1-280-12244-7 9786613526304 1-4398-6092-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Dedication; Contents; Preface; Acknowledgments; About the Author; 1. Introduction; 2. Two Basic Data Mining Methods for Variable Assessment; 3. CHAID-Based Data Mining for Paired-Variable Assessment; 4. The Importance of Straight Data: Simplicity and Desirability for Good Model-Building Practice; 5. Symmetrizing Ranked Data: A Statistical Data Mining Method for Improving the Predictive Power of Data; 6. Principal Component Analysis: A Statistical Data Mining Method for Many-Variable Assessment; 7. The Correlation Coefficient: Its Values Range between Plus/Minus 1, or Do They?
8. Logistic Regression: The Workhorse of Response Modeling9. Ordinary Regression: The Workhorse of Profit Modeling; 10. Variable Selection Methods in Regression: Ignorable Problem, Notable Solution; 11. CHAID for Interpreting a Logistic Regression Model; 12. The Importance of the Regression Coefficient; 13. The Average Correlation: A Statistical Data Mining Measure for Assessment of Competing Predictive Models and the Importance of the Predictor Variables; 14. CHAID for Specifying a Model with Interaction Variables; 15. Market Segmentation Classification Modeling with Logistic Regression 16. CHAID as a Method for Filling in Missing Values17. Identifying Your Best Customers: Descriptive, Predictive, and Look-Alike Profiling; 18. Assessment of Marketing Models; 19. Bootstrapping in Marketing: A New Approach for Validating Models; 20. Validating the Logistic Regression Model: Try Bootstrappin; 21. Visualization of Marketing ModelsData Mining to Uncover Innards of a Model; 22. The Predictive Contribution Coefficient: A Measure of Predictive Importance; 23. Regression Modeling Involves Art, Science, and Poetry, Too; 24. Genetic and Statistic Regression Models: A Comparison 25. Data Reuse: A Powerful Data Mining Effect of the GenIQ Model26. A Data Mining Method for Moderating Outliers Instead of Discarding Them; 27. Overfitting: Old Problem, New Solution; 28. The Importance of Straight Data: Revisited; 29. The GenIQ Model: Its Definition and an Application; 30. Finding the Best Variables for Marketing Models; 31. Interpretation of Coefficient-Free Models |
Record Nr. | UNINA-9910821503903321 |
Ratner Bruce
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Boca Raton : , : Taylor & Francis, , 2012 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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Statistical learning for big dependent data / / Daniel Peña, Ruey S. Tsay |
Autore | Peña Daniel <1948-> |
Edizione | [First edition.] |
Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
Descrizione fisica | 1 online resource (563 pages) |
Disciplina | 005.7 |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Big data - Mathematics
Time-series analysis Data mining - Statistical methods Forecasting - Statistical methods |
ISBN |
1-119-41741-4
1-119-41740-6 1-119-41739-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Introduction to big dependent data -- Linear univariate time series -- Analysis of multivariate time series -- Handling heterogeneity in many time series -- Clustering and classification of time series -- Dynamic factor models -- Forecasting with big dependent data -- Machine learning of big dependent data -- Spatio-temporal dependent data. |
Record Nr. | UNINA-9910829984503321 |
Peña Daniel <1948->
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Hoboken, New Jersey : , : Wiley, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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La Théorie de l'analyse Statistique Implicative Ou l'invraisemblance du Faux / / Régis Gras |
Autore | Gras Régis |
Pubbl/distr/stampa | Toulouse : , : Cepadues Editions, , [2018] |
Descrizione fisica | 1 online resource (232 pages) |
Disciplina | 006.312 |
Soggetto topico | Data mining - Statistical methods |
Soggetto genere / forma | Electronic books. |
ISBN | 2-36493-700-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | fre |
Record Nr. | UNINA-9910467535003321 |
Gras Régis
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Toulouse : , : Cepadues Editions, , [2018] | ||
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Lo trovi qui: Univ. Federico II | ||
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La Théorie de l'analyse Statistique Implicative Ou l'invraisemblance du Faux / / Régis Gras |
Autore | Gras Régis |
Pubbl/distr/stampa | Toulouse : , : Cepadues Editions, , [2018] |
Descrizione fisica | 1 online resource (232 pages) |
Disciplina | 006.312 |
Soggetto topico | Data mining - Statistical methods |
ISBN | 2-36493-700-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | fre |
Record Nr. | UNINA-9910793306703321 |
Gras Régis
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Toulouse : , : Cepadues Editions, , [2018] | ||
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Lo trovi qui: Univ. Federico II | ||
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La Théorie de l'analyse Statistique Implicative Ou l'invraisemblance du Faux / / Régis Gras |
Autore | Gras Régis |
Pubbl/distr/stampa | Toulouse : , : Cepadues Editions, , [2018] |
Descrizione fisica | 1 online resource (232 pages) |
Disciplina | 006.312 |
Soggetto topico | Data mining - Statistical methods |
ISBN | 2-36493-700-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | fre |
Record Nr. | UNINA-9910819905503321 |
Gras Régis
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Toulouse : , : Cepadues Editions, , [2018] | ||
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Lo trovi qui: Univ. Federico II | ||
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WSDM '15 : proceedings of the Eighth ACM International Conference on Web Search and Data Mining : Jan. 31-Feb. 6, 2015, Shanghai, China / / edited by Xueqi Cheng [and three others] |
Pubbl/distr/stampa | New York : , : ACM, , 2015 |
Descrizione fisica | 1 online resource (466 pages) |
Disciplina | 006.312 |
Soggetto topico |
Data mining
Data mining - Statistical methods |
ISBN | 1-4503-3317-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910375747403321 |
New York : , : ACM, , 2015 | ||
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Lo trovi qui: Univ. Federico II | ||
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