C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning: neural networks, genetic algorithms, and fuzzy systems
Machine learning: neural networks, genetic algorithms, and fuzzy systems
A simple but powerful heuristic method for generating fuzzy rules from numerical data
Fuzzy Sets and Systems
A high performance k-NN classifier using a binary correlation matrix memory
Proceedings of the 1998 conference on Advances in neural information processing systems II
RAM-Based Neural Networks
A Neural Architecture for Fast Rule Matching
ANNES '95 Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems
A binary neural k-nearest neighbour technique
Knowledge and Information Systems
A Comparative Study of Fuzzy Classifiers on Breast Cancer Data
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
A fuzzy systems framework for solving real world problems
WSEAS TRANSACTIONS on SYSTEMS
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This paper describes a binary neural network classifier that is able to make decisions based on fuzzy relational rule sets. Rule sets are extracted from a training data set and stored in a Correlation Matrix Memory (CMM). Such a classifier has many advantages including suitability for hardware implementations, fast matching, handling of missing or erroneous data and online learning. The main purpose of this paper is to demonstrate the suitability of the AURA library for building CMMs that perform fuzzy operations.