Name
Abstract | ||
|---|---|---|
Decision tree induction algorithms are well known techniques for assigning objects to predefined categories in a transparent fashion. Most decision tree induction algorithms rely on a greedy top-down recursive strategy for growing the tree, and pruning techniques to avoid overfitting. Even though such a strategy has been quite successful in many problems, it falls short in several others. For instance, there are cases in which the hyper-rectangular surfaces generated by these algorithms can only map the problem description after several sub-sequential partitions, which results in a large and incomprehensible tree. Hence, we propose a new decision tree induction algorithm based on clustering which seeks to provide more accurate models and/or shorter descriptions more comprehensible for the end-user. We do not base our performance analysis solely on the straightforward comparison of our proposed algorithm to baseline methods. Instead, we propose a data-dependent analysis in order to look for evidences which may explain in which situations our algorithm outperforms a well-known decision tree induction algorithm. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISDA.2011.6121712 | Intelligent Systems Design and Applications |
Keywords | Field | DocType |
data analysis,decision trees,learning (artificial intelligence),pattern clustering,clustering-based decision tree induction algorithm,data-dependent analysis,greedy top-down recursive strategy,hyper-rectangular surfaces,pruning techniques,transparent fashion,clustering,data-dependency analysis,decision trees,hybrid intelligent systems,machine learning | Decision tree,Data mining,Computer science,Order statistic tree,Artificial intelligence,ID3 algorithm,Decision stump,Tree traversal,Pattern recognition,Algorithm,Decision tree model,Decision tree learning,Machine learning,Incremental decision tree | Conference |
ISSN | ISBN | Citations |
2164-7143 | 978-1-4577-1676-8 | 1 |
PageRank | References | Authors |
0.36 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rodrigo C. Barros | 1 | 1 | 0.36 |
| André Carlos Ponce de Leon Ferreira de Carvalho | 2 | 30 | 2.68 |
| Márcio P. Basgalupp | 3 | 1 | 0.36 |
| Marcos Quiles | 4 | 16 | 3.01 |