Name
Abstract | ||
|---|---|---|
A machine learning system is useful for extracting models from data that can be used for many applications such as data analysis, decision support or data mining. SMILES is a machine learning system that integrates many different features from other machine learning techniques and paradigms, and more importantly, it presents several innovations in almost all of these features, such as ensemble methods, cost-sensitive learning, and the generation of a comprehensible model from an ensemble. This paper contains a short description of the main features of the system as well as some experimental results. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-45757-7_48 | JELIA |
Keywords | Field | DocType |
cost-sensitive learning,data mining,data analysis,decision support,comprehensible model,short description,main feature,different feature,multi-purpose learning system,ensemble method,machine learning,decision tree learning | Online machine learning,Stability (learning theory),Instance-based learning,Multi-task learning,Active learning (machine learning),Computer science,Unsupervised learning,Artificial intelligence,Computational learning theory,Ensemble learning,Machine learning | Conference |
Volume | ISSN | ISBN |
2424 | 0302-9743 | 3-540-44190-5 |
Citations | PageRank | References |
3 | 1.84 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Victor Estruch | 1 | 3 | 1.84 |
| C'esar Ferri | 2 | 688 | 62.37 |
| Jose Hernandez-orallo | 3 | 995 | 100.10 |
| M. José Ramírez-Quintana | 4 | 81 | 11.42 |