Information-Statistical Data Mining
Springer-Verlag New York Inc.
978-1-4020-7650-3 (ISBN)
Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
1. Preview: Data Warehousing/Mining.- 1. What is Summary Information?.- 2. Data, Information Theory, Statistics.- 3. Data Warehousing/Mining Management.- 4. Architecture, Tools and Applications.- 5. Conceptual/Practical Mining Tools.- 6. Conclusion.- 2. Data Warehouse Basics.- 1. Methodology.- 2. Conclusion.- 3. CONCEPT OF PATTERNS & VISUALIZATION.- 1. Introduction.- Appendix: Word Problem Solution.- 4. Information Theory & Statistics.- 1. Introduction.- 2. Information Theory.- 3. Variable Interdependence Measure.- 4. Probability Model Comparison.- 5. Pearson’s Chi-Square Statistic.- 5. Information and Statistics Linkage.- 1. Statistics.- 2. Concept Of Information.- 3. Information Theory And Statistics.- 4. Conclusion.- 6. Temporal-Spatial Data.- 1. Introduction.- 2. Temporal-Spatial Characteristics.- 3. Temporal-Spatial Data Analysis.- 4. Problem Formulation.- 5. Temperature Analysis Application.- 6. Discussion.- 7. Conclusion.- 7. Change Point Detection Techniques.- 1. Change Point Problem.- 2. Information Criterion Approach.- 3. Binary Segmentation Technique.- 4. Example.- 5. Summary.- 8. Statistical Association Patterns.- 1. Information-Statistical Association.- 2. Conclusion.- 9. Pattern Inference & Model Discovery.- 1. Introduction.- 2. Concept Of Pattern-Based Inference.- 3. Conclusion.- Appendix: Pattern Utility Illustration.- 10. Bayesian Nets & Model Generation.- 1. Preliminary Of Bayesian Networks.- 2. Pattern Synthesis for Model Learning.- 3. Conclusion.- 11. Pattern Ordering Inference: Part I.- 1. Pattern Order Inference Approach.- 2. Bayesian Net Probability Distribution.- 3. Bayesian Model: Pattern Embodiment.- 4. RLCM for Pattern Ordering.- 12. Pattern Ordering Inference: Part II.- 1. Ordering General Event Patterns.- 2. Conclusion.- Appendix I: 51Largest PR(ADHJBCEF % MathType!MTEF!2!1!+-
% feaagaart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn
% hiov2DGi1BTfMBaeXatLxBI9gBqj3BWbIqubWexLMBb50ujbqegm0B
% 1jxALjharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqr
% Ffpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0F
% irpepeKkFr0xfr-xfr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaa
% GcbaWaa0aaaeaacaWGhbaaamaamaaabaGaamysaaaaaaa!3B22!
$$ /overline G /underline I $$.- Appendix II: Ordering of PR(LI/SE). SE=F G I.- Appendix III.A: Evaluation of Method A.- Appendix III.B: Evaluation of Method B.- Appendix III.C: Evaluation of Method C.- 13. Case Study 1: Oracle Data Warehouse.- 1. Introduction.- 2. Background.- 3. Challenge.- 4. Illustrations.- 5. Conclusion.- Appendix I: Warehouse Data Dictionary.- 14. Case Study 2: Financial Data Analysis.- 1. The Data.- 2. Information Theoretic Approach.- 3. Data Analysis.- 4. Conclusion.- 15. Case Study 3: Forest Classification.- 1. Introduction.- 2. Classifier Model Derivation.- 3. Test Data Characteristics.- 4. Experimental Platform.- 5. Classification Results.- 6. Validation Stage.- 7. Effect of Mixed Data on Performance.- 8. Goodness Measure for Evaluation.- 9. Conclusion.- References.
| Erscheint lt. Verlag | 30.11.2003 |
|---|---|
| Reihe/Serie | The Springer International Series in Engineering and Computer Science ; 757 |
| Zusatzinfo | XXII, 289 p. |
| Verlagsort | New York, NY |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Technik ► Maschinenbau | |
| ISBN-10 | 1-4020-7650-9 / 1402076509 |
| ISBN-13 | 978-1-4020-7650-3 / 9781402076503 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
