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Record Nr. |
UNINA9910337636303321 |
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Autore |
McCarthy Richard V. |
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Titolo |
Applying Predictive Analytics : Finding Value in Data / / by Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci, Leila Halawi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (X, 205 p.) |
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Disciplina |
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Soggetti |
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Electrical engineering |
Computational intelligence |
Data mining |
Big data |
Communications Engineering, Networks |
Computational Intelligence |
Data Mining and Knowledge Discovery |
Big Data/Analytics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction to Predictive Analytics -- Know Your Data – Data Preparation -- What do Descriptive Statistics Tell Us -- The First of the Big Three – Regression -- The Second of the Big Three – Decision Trees -- The Third of the Big Three - Neural Networks -- Model Comparisons and Scoring -- Appendix A -- Data Dictionary for the Automobile Insurance Claim Fraud Data Example -- Conclusion. |
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Sommario/riassunto |
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This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A |
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