Elements of an agile discovery environment

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2843, Issue , 2003, Pages 311-319

  Grigoriev, Peter A ^a   Yevtushenko, Serhiy A ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

DATA-MINING TOOLS; MACHINE LEARNING METHODS; MODERN TOOLS;

DATA MINING;

EID: 0242297820     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-39644-4_28     Document Type: Article

References (14)

1. Manifesto for agile software development, 2001. http://agilemanifesto.org/.
2. C. Piscopo and M. Birattari. Invention vs. discovery, a critical discussion. In Discovery Science. 5th International Conference, DS 2002, pages 457-462, Berlin, 2002. Springer Verlag.
3. Ben Shneiderman. Inventing discovery tools: Combining information visualization with data mining. In Discovery Science. 4th International Conference, DS 2001, pages 17-29, New York, 2001. Springer Verlag.
4. KD-Nuggets. Kdnuggets: Polls: Data mining tools you regularly use, June 2002. http://www.kdnuggets.com/polls/2002/data_mining_tools.htm.
5. http://www.spss.com/SPSSBI/Clementine/.
6. Weka 3: Machine learning software in Java. http://www.cs.waikato.ac.nz/ml/weka/.
7. http://www.sas.com.
8. http://www.salford-systems.com/products-cart.html.
9. http://www.spss.com.sg/products/answertree.htm.
10. Ronald de Wolf Shan-Hwei Nienhuys-Cheng. Foundations of inductive logic programming. Lecture notes in artificial intelligence. Springer, 1997.
11. Viktor Finn. Plausible reasoning of JSM-type in open (+/-) worlds. In Architectures for Semiotic Modeling and Situation Analysis in Large Complex Systems, Monterey, CA, USA, 1995.
12. http://ki-www2.intellektik.informatik.tu-darmstadt.de/∼jsm/QDA.
13. http://www.sgi.com/tech/mlc/.
14. Data Mining Group. Predictive model markup language (PMML). http://www.dmg.org/.