Handbook of statistical analysis and data mining applications. (©2009)

• Record Type: Book
• Other Titles: Handbook of statistical analysis & data mining applications
• Further Information: Note: Robert Nisbet, John Elder, Gary Miner.
• Other Names: Nisbet, Robert; Elder, John F (John Fletcher); Miner, Gary
• Contents: PART I: History of Phases of Data Analysis, Basic Theory, and the Data Mining Process -- Chapter 1. History -- The Phases of Data Analysis throughout the Ages -- Chapter 2. Theory -- Chapter 3. The Data Mining Process -- Chapter 4. Data Understanding and Preparation -- Chapter 5. Feature Selection -- Selecting the Best Variables -- Chapter 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 -- Chapter 7. Basic Algorithms -- Chapter 8: Advanced Algorithms -- Chapter 9. Text Mining -- Chapter 10. Organization of 3 Leading Data Mining Tools -- Chapter 11. Classification Trees = Decision Trees -- Chapter 12. Numerical Prediction (Neural Nets and GLM) -- Chapter 13. Model Evaluation and Enhancement -- Chapter 14. Medical Informatics -- Chapter 15. Bioinformatics -- Chapter 16. Customer Response Models -- Chapter 17. Fraud Detection -- PART III: Tutorials -- Step-by-Step Case Studies as a Starting Point to learn how to do Data Mining Analyses -- Listing of Guest Authors of the Tutorials -- Tutorials within the book pages: -- How to use the DMRecipe -- Aviation Safety using DMRecipe -- Movie Box-Office Hit Prediction using SPSS CLEMENTINE -- Bank Financial data -- using SAS-EM -- Credit Scoring -- CRM Retention using CLEMENTINE -- Automobile -- Cars -- Text Mining -- Quality Control using Data Mining -- Three integrated tutorials from different domains, but all using C & RT to predict and display possible structural relationships among data: -- Business Administration in a Medical Industry -- Clinical Psychology- Finding Predictors of Correct Diagnosis -- Education -- Leadership Training: for Business and Education -- Additional tutorials are available either on the accompanying CD-DVD, or the Elsevier Web site for this book -- Listing of Tutorials on Accompanying CD -- PART IV: Paradox of Complex Models; using the "right model for the right use", on-going development, and the Future. -- Chapter 18: Paradox of Ensembles and Complexity -- Chapter 19: The Right Model for the Right Use -- Chapter 20: The Top 10 Data Mining Mistakes -- Chapter 21: Prospect for the Future -- Developing Areas in Data Mining.
• Publisher Details: Amsterdam Boston : Academic Press/Elsevier
• Publication Date: 2009
• Copyright Date: 2009
• Extent: 1 online resource (xxxiv, 824 pages), illustrations (chiefly color)
• Subjects: 006.3/12; 004; Data mining -- Statistical methods; Exploration de données (Informatique) -- Méthodes statistiques; COMPUTERS -- Reference; COMPUTERS -- Machine Theory; COMPUTERS -- Computer Literacy; COMPUTERS -- Information Technology; COMPUTERS -- Data Processing; COMPUTERS -- Computer Science; COMPUTERS -- Database Management -- Data Mining; COMPUTERS -- Hardware -- General; Exploration de données -- Méthodes statistiques; Electronic books
• Languages: English
• ISBNs: 9780080912035; 0080912036
• Related ISBNs: 9780123747655; 0123747651
• Notes: Note: Includes bibliographical references and index.; Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.