Handbook of statistical analysis and data mining applications. (2017)

• Record Type: Book
• Editors: Nisbet, Robert; Miner, Gary; Yale, Ken
• Contents: PART I: History of Phases of Data Analysis, Basic Theory, and the Data Mining Process 1. History – The Phases of Data Analysis throughout the Ages 2. Theory 3. The Data Mining Process 4. Data Understanding and Preparation 5. Feature Selection – Selecting the Best Variables 6: Accessory Tools and Advanced Features in Data PART II: - The Algorithms in Data Mining and Text Mining, and the Organization of the Three most common Data Mining Tools 7. Basic Algorithms 8. Advanced Algorithms 9. Text Mining 10. Organization of 3 Leading Data Mining Tools 11. Classification Trees = Decision Trees 12. Numerical Prediction (Neural Nets and GLM) 13. Model Evaluation and Enhancement 14. Medical Informatics 15. Bioinformatics 16. Customer Response Models 17. Fraud Detection PART III: Tutorials - Step-by-Step Case Studies as a Starting Point to learn how to do Data Mining Analyses Tutorials PART IV: Paradox of Complex Models; using the “right model for the right use”, on-going development, and the Future 18. Paradox of Ensembles and Complexity 19. The Right Model for the Right Use 20. The Top 10 Data Mining Mistakes 21. Prospects for the Future – Developing Areas in Data Mining 22. Summary
• Edition: Second edition
• Publisher Details: Amsterdam : Academic Press
• Publication Date: 2017
• Extent: 1 online resource
• Subjects: 006.312015195; Data mining -- Statistical methods; Statistics
• Languages: English
• ISBNs: 9780124166455
• Related ISBNs: 9780124166325
• Notes: Note: Description based on CIP data; resource not viewed.
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