Mark F. (Sr. Manager, Data Mining Technologies, Oracle Corporation, Burlington, MA) Hornick
Meer over de auteurs
Mark F. (Sr. Manager, Data Mining Technologies, Oracle Corporation, Burlington, MA) Hornick,
Mark F. Hornick,
Erik (Founder and Chief Technical Officer, KXEN, Paris, France) Marcade,
Erik Marcadé,
Sunil (Principal Member of Technical Staff, Oracle, Burlington, MA) Venkayala,
Sunil Venkayala
e.a.
Java Data Mining: Strategy, Standard, and Practice
A Practical Guide for Architecture, Design, and Implementation
Paperback Engels 2006 9780123704528Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard.
Specificaties
ISBN13:9780123704528
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:544
Uitgever:Elsevier Science & Technology
Hoofdrubriek:Programmeren, Computer en informatica
Lezersrecensies
Wees de eerste die een lezersrecensie schrijft!
Inhoudsopgave
Part I - Strategy 1. Overview of Data Mining 2. Solving Problems in Industry 3. Data Mining Process 4. Mining Functions and Algorithms 5. JDM Strategy 6. Getting Started
Part II - Standard 7. Java Data Mining Concepts 8. Design of the JDM API 9. Using the JDM API 10. XML Schema 11. Web Services
Part III - Practice 12. Practical Problem Solving 13. Building Data Mining Tools using JDM 14. Getting Started with JDM Web Services 15. Impacts on IT Infrastructure 16. Vendor implementations
Part IV. Wrapping Up 17. Evolution of Data Mining Standards 18. Preview of Java Data Mining 2.0 19. Summary
A. Further Reading B. Glossary
Part II - Standard 7. Java Data Mining Concepts 8. Design of the JDM API 9. Using the JDM API 10. XML Schema 11. Web Services
Part III - Practice 12. Practical Problem Solving 13. Building Data Mining Tools using JDM 14. Getting Started with JDM Web Services 15. Impacts on IT Infrastructure 16. Vendor implementations
Part IV. Wrapping Up 17. Evolution of Data Mining Standards 18. Preview of Java Data Mining 2.0 19. Summary
A. Further Reading B. Glossary
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