Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Methods for combining experts' probability assessments
Neural Computation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
NEFCLASS-X — a Soft Computing Tool to Build Readable Fuzzy Classifiers
BT Technology Journal
Interpretation of Trained Neural Networks by Rule Extraction
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Experiments with Classifier Combining Rules
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
An effective combination of multiple classifiers for toxicity prediction
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
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The increasing amount and complexity of data in toxicity prediction calls for new approaches based on hybrid intelligent methods for mining the data. This focus is required even more in the context of increasing number of different classifiers applied in toxicity prediction. Consequently, there exist a need to develop tools to integrate various approaches. The goal of this research is to apply neuro-fuzzy networks to provide an improvement in combining the results of five classifiers applied in toxicity of pesticides. Nevertheless, fuzzy rules extracted from the trained developed networks can be used to perform useful comparisons between the performances of the involved classifiers. Our results suggest that the neuro-fuzzy approach of combining classifiers has the potential to significantly improve common classification methods for the use in toxicity of pesticides characterization, and knowledge discovery.