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" Data mining for scientific and engineering applications "
edited by Robert L. Grossman ... [et al.].
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BL
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| Record Number
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725734
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b545455
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| Main Entry
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edited by Robert L. Grossman ... [et al.].
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| Title & Author
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Data mining for scientific and engineering applications\ edited by Robert L. Grossman ... [et al.].
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| Publication Statement
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Dordrecht ; Boston ; London: Kluwer Academic, cop., 2001
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| Series Statement
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Massive computing, vol. 2.
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XX, 605 str. : ilustr. ; 24 cm.
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| ISBN
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1402000332
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: 1402001142
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: 9781402000331
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: 9781402001147
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| Contents
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Foreword. List of Contributors. List of Reviewers. Preface. 1. On Mining Scientific Datasets; C. Kamath. 2. Understanding High Dimensional and Large Data Sets: Some Mathematical Challenges and Opportunities; J. Chandra. 3. Data Mining at the Interface of Computer Science and Statistics; P. Smyth. 4. Mining Large Image Collections; M.C. Burl. 5. Mining Astronomical Databases; R.M. Humphreys, et al. 6. Searching for Bent-Double Galaxies in the First Survey; C. Kamath, et al. 7. A Dataspace Infrastructure for Astronomical Data; R. Grossman, et al. 8. Data Mining Applications in Bioinformatics; N. Ramakrishnan, A.Y. Grama. 9. Mining Residue Contacts in Proteins; M.J. Zaki, C. Bystroff. 10. KDD Services at the Goodard Earth Sciences Distributed Archive Center; C. Lynnes, R. Mack. 11. Data Mining in Integrated Data Access and Data Analysis Systems; R. Yang, et al. 12. Spatial Data Mining for Classification, Visualisation and Interpretation with Artmap Neural Network; W. Liu, et al. 13. Real Time Feature Extraction for the Analysis of Turbulent Flows; I. Marusic, et al. 14. Data Mining for Turbulent Flows; E.-H. Han, et al. 15. Evita-Efficient Visualization and Interrogation of Tera-Scale Data; R. Machiraju, et al. 16. Towards Ubiquitous Mining of Distributed Data; H. Kargupta, et al. 17. Decomposable Algorithms for Data Mining; R. Bhatnagar. 18. HDDI (R): Hierarchical Distributed Dynamic Indexing; W.M. Pottenger, et al.19. Parallel Algorithms for Clustering High-Dimensional Large-Scale Datasets; H. Nagesh, et al. 20. Efficient Clustering of Very Large Document Collections; I.S. Dhillon, et al. 21. A Scalable Hierarchical Algorithm for Unsupervised Clustering; D. Boley. 22. High-Performance Singular Value Decomposition; D.B. Skillicorn, X. Yang. 23. Mining High-Dimensional Scientific Data Sets Using Singular Value Decomposition; E. Maltseva, et al. 24. Spatial Dependence in Data Mining; J.P. LeSage, R.K. Pace. 25. Sparc: Spatial Association Rule-Based Classification; J. Han, et al. 26. What's Spatial About Spatial Data Mining: Three Case Studies; S. Shekhar, et al. 27. Predicting Failures in Event Sequences; M.J. Zaki, et al. 28. Efficient Algorithms for Mining Long Patterns in Scientific Data Sets; R.C. Agarwal, C.C. Aggarwal. 29. Probabilistic Estimation in Data Mining; E.P.D. Pednault, C. Apte. 30. Classification Using Association Rules: Weaknesses and Enhancements; B. Liu, et al.
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| Subject
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Data mining.
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| Subject
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rudarjenje podatkov -- umetna inteligenca -- algoritmi
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| LC Classification
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QA76.9.D343E358 2001
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| Added Entry
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et al
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Robert L Grossman
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