Organizing the World's Machine Learning Information

Communications in Computer and Information Science

Volumn 17, Issue , 2009, Pages 693-708

  Vanschoren, Joaquin ^a   Blockeel, Hendrik ^a   Pfahringer, Bernhard ^b   Holmes, Geoff ^b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

BIRD'S EYE VIEW; DATA-MINING TOOLS;

COMPUTER SCIENCE;

EXPERIMENTS;

EID: 70349960753     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: None     Document Type: Article

References (16)

1. Allison, L.: Models for machine learning and data mining in functional programming. Journal of Functional Programming 15(1), 15-32 (2005)
2. Ball, C.A., Brazma, A., Causton, H., Chervitz, S., Edgar, R., et al.: Submission of Microarray Data to Public Repositories. PLoS Biol. 2(9), e317 (2004)
3. Blockeel, H.: Experiment databases: A novel methodology for experimental research. In: Bonchi, F., Boulicaut, J.-F. (eds.) KDID 2005. LNCS, vol. 3933, pp. 72-85. Springer, Heidelberg (2006)
4. Blockeel, H., Vanschoren, J.: Experiment databases: Towards an improved experimental methodology in machine learning. In: Kok, J.N., Koronacki, J., López de Mántaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) PKDD 2007. LNCS (LNAI), vol. 4702, pp. 6-17. Springer, Heidelberg (2007)
5. Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., et al.: Minimum information about a microarray experiment (MIAME): toward standards for microarray data. Nature Genetics 29, 365-371 (2001)
6. Brazma, A., Parkinson, H., Sarkans, U., Shojatalab, M., et al.: ArrayExpress-a public repository for microarray gene expression data at the EBI. Nucleic Acids Research 31(1), 68-71 (2003)
7. Caruana, R., Niculescu-Mizil, A.: An empirical comparison of supervised learning algorithms. In: Airoldi, E.M., Blei, D.M., Fienberg, S.E., Goldenberg, A., Xing, E.P., Zheng, A.X. (eds.) ICML 2006. LNCS, vol. 4503, pp. 161-168. Springer, Heidelberg (2007)
8. The Data Mining Group: The Predictive Model Markup Language (PMML), version 3.2, http://www.dmg.org/pmml-v3-2.html
9. Demšar, J.: Statistical Comparisons of Classifiers over Multiple Data Sets. Journal of Machine Learning Research 7, 1-30 (2006)
10. Džeroski, S.: Towards a General Framework for Data Mining. In: Džeroski, S., Struyf, J. (eds.) KDID 2006. LNCS, vol. 4747, pp. 259-300. Springer, Heidelberg (2007)
11. Imielinski, T., Mannila, H.: A database perspective on knowledge discovery. Communications of the ACM 39(11), 58-64 (1996)
12. Perlich, C., Provost, F., Siminoff, J.: Tree induction vs. logistic regression: A learning curve analysis. Journal of Machine Learning Research 4, 211-255 (2003)
13. Soldatova, L.N., Clare, A., Sparkes, A., King, R.D.: An ontology for a Robot Scientist. Bioinformatics 22(14), 464-471 (2006)
14. Stoeckert, C., Causton, H., Ball, C.: Microarray databases: standards and ontologies. Nature Genetics 32, 469-473 (2002)
15. Vanschoren, J., Pfahringer, B., Holmes, G.: Learning From The Past with Experiment Databases. Working Paper Series 08/2008, Computer Science Department, University of Waikato (2008)
16. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)