Name
Abstract | ||
|---|---|---|
A data driven methodology to automatically derive a Fuzzy Logic Classifier (FLC) only on the basis of the raw signals available, is proposed. The first step is a feature selection performed with the approach of Classification and Regression Trees (CART), to extract the variables in the database which are the most critical for the problem under study. Then a CART is produced using only the previously selected features and is provided to a fully automated algorithm which determines the membership functions and the most appropriate rules to reproduce the classification tree obtained with CART. The resulting FLC attains good performance in terms of generalization and classification, still providing a set of rules which can be easily interpreted in order to achieve a first, intuitive understanding of the phenomenon involved. To assess the potentiality of the approach, the method has been applied to a synthetic database provided for the NIPS 2003 feature selection competition and to a real classification problem. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IJCNN.2009.5178855 | IJCNN |
Keywords | Field | DocType |
feature selection,fuzzy logic classifier,synthetic database,real classification problem,automated algorithm,cart data analysis,good performance,appropriate rule,regression trees,classification tree,feature selection competition,data analysis,membership function,decision trees,fuzzy logic,data mining,silicon,fuzzy systems,regression analysis,fuzzy sets | Decision tree,Data mining,Feature selection,Computer science,Fuzzy set,Artificial intelligence,Fuzzy control system,Classifier (linguistics),Interpretability,Pattern recognition,Fuzzy logic,Decision tree learning,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guido Vagliasindi | 1 | 11 | 2.58 |
| Paolo Arena | 2 | 261 | 47.43 |
| Andrea Murari | 3 | 0 | 1.69 |