Extraction and optimization of classification rules for continuous or mixed mode data using neural nets

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4384, Issue , 2001, Pages 38-45

  Wang, D ^a   Dillon, T S ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Classification; Data mining; Regularization; Rule generation; Self organizing networks

Indexed keywords

COGNITIVE SYSTEMS; DATABASE SYSTEMS; LEARNING ALGORITHMS; OPTIMIZATION; PATTERN RECOGNITION; PROBABILITY; SELF ORGANIZING MAPS;

SELF-ORGANIZING NETWORKS;

DATA MINING;

EID: 0034934995     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.421090     Document Type: Conference Paper

References (17)

1. Database Mining: A performance perspective
2. From data mining to knowledge discovery in databases
3. Using single-layered neural networks for the extraction of conjunctive rules and hierarchical classifications
4. Effective data mining using neural networks
5. Automated knowledge acquisition using unsupervised learning
6. Hybrid BRAINNE: A method for developing symbolic rules from hybrid neural network
7. Knowledge-based fuzzy MLP for classification and rule generation
8. A fuzzy classifier with ellipsoidal regions
9. Extracting refined rules from knowledge-based neural networks
10. A neural-network model for learning domain rules based on its activation function characteristics
11. Are artificial neural networks black boxes?
12. Symbolic interpretation of artificial neural networks
13. A regularized iterative image restoration algorithm
14. The "Weight smoothing" regularization of MLP for Jacobian stabilization
15. Enhancing the estimation of plant Jacobian for adaptive neural inverse control