Extracting Refined Rules from Knowledge-Based Neural Networks
Machine Learning
Data mining with neural networks: solving business problems from application development to decision support
Elements of artificial neural networks
Elements of artificial neural networks
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Generalized Analytic Rule Extraction for Feedforward Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Extracting Provably Correct Rules from Artificial Neural Networks
Extracting Provably Correct Rules from Artificial Neural Networks
Knowledge discovery using neural networks
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Applying fuzzy neural network to estimate software development effort
Applied Intelligence
An intelligent decision-support model using FSOM and rule extraction for crime prevention
Expert Systems with Applications: An International Journal
Reverse Engineering the Neural Networks for Rule Extraction in Classification Problems
Neural Processing Letters
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A novel knowledge discovery technique using neural networks is presented. A neural network is trained to learn the correlations and relationships that exist in a dataset. The neural network is then pruned and modified to generalize the correlations and relationships. Finally, the neural network is used as a tool to discover all existing hidden trends in four different types of crimes (murder, rape, robbery, and auto theft) in US cities as well as to predict trends based on existing knowledge inherent in the network.