Communications of the ACM
Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Symbolic knowledge extraction from trained neural networks: a sound approach
Artificial Intelligence
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
FERNN: An Algorithm for Fast Extraction of Rules fromNeural Networks
Applied Intelligence
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Extract intelligible and concise fuzzy rules from neural networks
Fuzzy Sets and Systems - Fuzzy systems
Learning to detect texture objects by artificial immune approaches
Future Generation Computer Systems - Special issue: Geocomputation
Classification with incomplete survey data: a Hopfield neural network approach
Computers and Operations Research
IEEE Transactions on Knowledge and Data Engineering
Neural network explanation using inversion
Neural Networks
Anomaly detection in TCP/IP networks using immune systems paradigm
Computer Communications
Expert Systems with Applications: An International Journal
Data mining with a simulated annealing based fuzzy classification system
Pattern Recognition
Design of a hybrid system for the diabetes and heart diseases
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Extraction of rules from artificial neural networks for nonlinear regression
IEEE Transactions on Neural Networks
Fuzzy min-max neural networks. I. Classification
IEEE Transactions on Neural Networks
Knowledge based Least Squares Twin support vector machines
Information Sciences: an International Journal
Data mining via rules extracted from GMDH: an application to predict churn in bank credit cards
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Run-time malware detection based on positive selection
Journal in Computer Virology
The evaluation of intelligent agent performance - An example of B2C e-commerce negotiation
Computer Standards & Interfaces
A case study of muscle dysmorphia disorder diagnostics
Expert Systems with Applications: An International Journal
A hybrid intelligent system for medical data classification
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Although Artificial Neural Network (ANN) usually reaches high classification accuracy, the obtained results in most cases may be incomprehensible. This fact is causing a serious problem in data mining applications. The rules that are derived from ANN are needed to be formed to solve this problem and various methods have been improved to extract these rules. In our previous work, a hybrid neural network was presented for classification (Kahramanli & Allahverdi, 2008). In this study a method that uses Artificial Immune Systems (AIS) algorithm has been presented to extract rules from trained hybrid neural network. The data were obtained from the University of California at Irvine (UCI) machine learning repository. The datasets are Cleveland heart disease and Hepatitis data. The proposed method achieved accuracy values 96.4% and 96.8% for Cleveland heart disease dataset and Hepatitis dataset respectively. It is been observed that these results are one of the best results comparing with results obtained from related previous studies and reported in UCI web sites.