Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
Communications of the ACM
Computer
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Models of incremental concept formation
Artificial Intelligence
Neurocomputing
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural network approaches to automated knowledge extraction from raw data
Neural network approaches to automated knowledge extraction from raw data
Linear Algebra Approach to Neural Associative Memories and Noise performance of Neural Classifiers
IEEE Transactions on Computers - Special issue on artificial neural networks
Expert Systems with Applications: An International Journal
Contributions of domain knowledge and stacked generalization in AI-Based classification models
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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A paradigm for diagnostic neural network systems that emphasizes informative data representation and encoding and uses generic preprocessing techniques to extract knowledge from database records is discussed. The proposed diagnostic system differs from other approaches to automatic knowledge extraction in the following ways: by emphasizing the importance of intelligent encoding and preprocessing of raw data, rather than classifications; by demonstrating the importance of making a clear distinction between diagnostic and classification tasks; and by providing a generic, uniform representation for data records comprising interdependent, heterogeneous features. The correlation matrix memory (CMM), a linear system with a single-layer of input-output connections, that is used as the neural network system's classifier is described. The limitations of the learning system are discussed.