Self-organization and associative memory: 3rd edition
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The nature of statistical learning theory
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Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Forecasting S&P 500 stock index futures with a hybrid AI system
Decision Support Systems
Document clustering for electronic meetings: an experimental comparison of two techniques
Decision Support Systems - From information retrieval to knowledge management: enabling technologies and best practices
Feature Selection for Knowledge Discovery and Data Mining
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On Comparing Classifiers: Pitfalls toAvoid and a Recommended Approach
Data Mining and Knowledge Discovery
Backpropagation and Recurrent Neural Networks in Financial Analysis of Multiple Stock Market Returns
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 2: Decision Support and Knowledge-Based Systems
A Hybrid SOM-SVM Method for Analyzing Zebra Fish Gene Expression
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Stock market prediction using artificial neural networks with optimal feature transformation
Neural Computing and Applications
Forecasting stock market movement direction with support vector machine
Computers and Operations Research
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Application of support vector machines to corporate credit rating prediction
Expert Systems with Applications: An International Journal
A hybrid approach for improving predictive accuracy of collaborative filtering algorithms
User Modeling and User-Adapted Interaction
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
A study of Taiwan's issuer credit rating systems using support vector machines
Expert Systems with Applications: An International Journal
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
A new SOM algorithm for electricity load forecasting
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Support vector machine with adaptive parameters in financial time series forecasting
IEEE Transactions on Neural Networks
Feature Selection Using a Piecewise Linear Network
IEEE Transactions on Neural Networks
Grey system theory-based models in time series prediction
Expert Systems with Applications: An International Journal
Flood disaster loss comprehensive evaluation model based on optimization support vector machine
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Stock trend prediction based on fractal feature selection and support vector machine
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Single-step ahead prediction based on the principle of concatenation using grey predictors
Expert Systems with Applications: An International Journal
Speedup of color palette indexing in self-organization of Kohonen feature map
Expert Systems with Applications: An International Journal
A hybrid stock selection model using genetic algorithms and support vector regression
Applied Soft Computing
An efficient CMAC neural network for stock index forecasting
Expert Systems with Applications: An International Journal
A stock selective system by using hybrid models of classification
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Computers & Mathematics with Applications
Hi-index | 12.06 |
Stock market price index prediction is regarded as a challenging task of the financial time series prediction process. Support vector regression (SVR) has successfully solved prediction problems in many domains, including the stock market. This paper hybridizes SVR with the self-organizing feature map (SOFM) technique and a filter-based feature selection to reduce the cost of training time and to improve prediction accuracies. The hybrid system conducts the following processes: filter-based feature selection to choose important input attributes; SOFM algorithm to cluster the training samples; and SVR to predict the stock market price index. The proposed model was demonstrated using a real future dataset - Taiwan index futures (FITX) to predict the next day's price index. The experiment results show that the proposed SOFM-SVR is an improvement over the traditional single SVR in average prediction accuracy and training time.