Handbook of Statistical Analysis and Data Mining ApplicationsAcademic Press, 14/05/2009 - 864 páginas The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. - Written "By Practitioners for Practitioners" - Non-technical explanations build understanding without jargon and equations - Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models - Practical advice from successful real-world implementations - Includes extensive case studies, examples, MS PowerPoint slides and datasets - CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book |
Índice
| 1 | |
The Algorithms in Data Mining and Text Mining the Organization of the Three most common Data Mining Tools and Selecte | 119 |
TutorialsStepbyStep Case Studies as a Starting Point to learn how to do Data Mining Analyses | 363 |
Measuring true complexity the Right Model for the Right Use Top Mistakes and the Future of Analytics | 705 |
| 789 | |
| 801 | |
DVD Install Instructions | 823 |
Outras edições - Ver tudo
Handbook of Statistical Analysis and Data Mining Applications Ken Yale,Robert Nisbet,Gary D. Miner Pré-visualização limitada - 2017 |
Handbook of Statistical Analysis and Data Mining Applications Robert Nisbet,John Fletcher Elder,Gary Miner Pré-visualização indisponível - 2009 |
Handbook of Statistical Analysis and Data Mining Applications Robert Nisbet,Gary Miner,Ken Yale Pré-visualização indisponível - 2017 |
Palavras e frases frequentes
accuracy algorithms analytical approach bioinformatics boosted trees button C&RT CHAID Chapter Clementine clusters complex computing Configure all steps create CRISP-DM cross-validation data file Data miner recipes Data Miner Workspace data mining data mining algorithms Data Mining Applications data mining tools Data preparation Data redundancy data set Data Source database decision tree default dependent variable Deployment dialog distribution DMRecipe documents error Evaluation example Feature Selection frequency graph input data Interactive interface lift chart machine learning MARSplines medical informatics methods Model building multiple neural net Neural Network nonlinear output p-value parameters patterns PMML predictive models predictor variables problem Profit Random forest relationships sample SAS-EM Select variables shown in Figure split spreadsheet STATISTICA Data Miner Statistical Analysis StatSoft Steps Options Support Vector Machines Table target variable techniques text mining training data transformations Tutorial Type values Variable selection window words Workbook
