Name
Title | ||
|---|---|---|
Using An Evolutionary Strategy to Select Input Features for a Neural Network Classifier |
Abstract | ||
|---|---|---|
Modelling in high dimensional spaces is usually following a feature selection process. Feature selection and feature creation
are two of the most important and difficult tasks in the field of pattern recognition. It involves determination of a good
feature subset, given a set of feature candidates. The present method is one approach to improve the pattern classification
performance using a feature selection process in conjunction with a neural network classifier an implied feed forward architecture.
The feature selection part is based on an evolutionary strategy and the subsequent classification step. Both have been combined.
|
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/978-94-010-0324-7_12 | Advances in Computational Intelligence and Learning |
Keywords | Field | DocType |
evolutionary strategy,feature selection,select input features,neural network classifier,neural networks,feed forward,pattern recognition,neural network | Neural network classifier,Pattern recognition,Feature selection,Computer science,Probabilistic neural network,Evolution strategy,Time delay neural network,Artificial intelligence,Artificial neural network,Machine learning,Feed forward | Conference |
ISBN | Citations | PageRank |
0-7923-7645-5 | 0 | 0.34 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jens Strackeljan | 1 | 5 | 1.69 |
| Andreas Schubert | 2 | 25 | 6.92 |