Name
Title | ||
|---|---|---|
Discovery of Significant Classification Rules from Incrementally Inducted Decision Tree Ensemble for Diagnosis of Disease |
Abstract | ||
|---|---|---|
Previous studies show that using significant classification rules to accomplish the classification task is suitable for bio-medical research. Discovery of many significant rules could be performed by using ensemble methods in decision tree induction. However, those traditional approaches are not useful for incremental task. In this paper, we use an ensemble method named Cascading and Sharing to derive many significant classification rules from incrementally inducted decision tree and improve the classifiers accuracy. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-03348-3_60 | ADMA |
Keywords | Field | DocType |
incrementally inducted decision tree,incremental task,significant classification rules,previous study,classification task,classifiers accuracy,bio-medical research,significant classification rule,ensemble method,significant rule,decision tree induction,decision tree | Decision tree,Data mining,Computer science,Artificial intelligence,Ensemble learning,Machine learning,Decision tree learning,Incremental decision tree,Decision stump | Conference |
Volume | ISSN | Citations |
5678 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minghao Piao | 1 | 37 | 6.30 |
| Jong Bum Lee | 2 | 1 | 1.03 |
| Khalid E. Saeed | 3 | 0 | 0.34 |
| Keun Ho Ryu | 4 | 883 | 85.61 |