A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Boosting a weak learning algorithm by majority
Information and Computation
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Probabilistic incremental program evolution
Evolutionary Computation
NeC4.5: Neural Ensemble Based C4.5
IEEE Transactions on Knowledge and Data Engineering
Expert Systems with Applications: An International Journal
Time-series forecasting using flexible neural tree model
Information Sciences: an International Journal
Research of neural network classifier based on FCM and PSO for breast cancer classification
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
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The combination of Further Division of Partition Space (FDPS) and Flexible Neural Tree (FNT) is proposed to improve the neural network classification performance. FDPS, which divides partition space into many partitions that will attach to different classes automatically, is a novel technique for neural network classification. FNT is a neural network's structure which uses flexible tree model. The proposed method combines FDPS and FNT to overcome their respective problems by using the other's merit. In order to evaluate the performance of this method, four well-known data sets are used for classification test. Experiment results have shown that this method has favorable performance.