The Use of Neural Networks in the Prediction of the Stock Exchange of Thailand (SET) Index
CIMCA '08 Proceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation
Stock Exchange of Thailand Index Prediction Using Back Propagation Neural Networks
ICCNT '10 Proceedings of the 2010 Second International Conference on Computer and Network Technology
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
BP Neural Network Model Based on the K-Means Clustering to Predict the Share Price
CSO '12 Proceedings of the 2012 Fifth International Joint Conference on Computational Sciences and Optimization
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A major drawback of artificial neural network is long training time depending on a number of training data. Thus, the contribution of this work is to present the intelligent hybrid system for faster training on neural network. The concept of the proposed method is applying DBSCAN for removing noise and outliers then selecting the represented instances to form a smaller training set for further model training. The experimental results indicate that the proposed method can dramatically reduce a size of training set while the predictive performance of the classifiers are better or almost the same as models trained with original training sets.