Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Neural networks in business: techniques and applications for the operations researcher
Computers and Operations Research - Neural networks in business
Feature selection on hierarchy of web documents
Decision Support Systems - Web retrieval and mining
Hybrid Intelligent Systems for Stock Market Analysis
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
An introduction to variable and feature selection
The Journal of Machine Learning Research
Decision Support Systems - Special issue: Data mining for financial decision making
Decision Support Systems - Special issue: Data mining for financial decision making
A hybrid model for exchange rate prediction
Decision Support Systems
Design and implementation of NN5 for Hong Kong stock price forecasting
Engineering Applications of Artificial Intelligence
A TSK type fuzzy rule based system for stock price prediction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A type-2 fuzzy rule-based expert system model for stock price analysis
Expert Systems with Applications: An International Journal
Review: Neural networks and statistical techniques: A review of applications
Expert Systems with Applications: An International Journal
A hybrid SOFM-SVR with a filter-based feature selection for stock market forecasting
Expert Systems with Applications: An International Journal
Evolving and clustering fuzzy decision tree for financial time series data forecasting
Expert Systems with Applications: An International Journal
Short-term stock price prediction based on echo state networks
Expert Systems with Applications: An International Journal
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
Feature selection in bankruptcy prediction
Knowledge-Based Systems
Asymmetric Principal Component and Discriminant Analyses for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining Methods and Models
Data Mining Methods and Models
Sliding window-based frequent pattern mining over data streams
Information Sciences: an International Journal
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
The use of data mining and neural networks for forecasting stock market returns
Expert Systems with Applications: An International Journal
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
Mining stock market tendency using GA-Based support vector machines
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Feature Selection Using a Piecewise Linear Network
IEEE Transactions on Neural Networks
Comparative analysis of data mining methods for bankruptcy prediction
Decision Support Systems
Determinants of intangible assets value: The data mining approach
Knowledge-Based Systems
Efficient classifiers for multi-class classification problems
Decision Support Systems
Trading team composition for the intraday multistock market
Decision Support Systems
Stock indices prediction using radial basis function neural network
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Prediction of movement direction in crude oil prices based on semi-supervised learning
Decision Support Systems
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To effectively predict stock price for investors is a very important research problem. In literature, data mining techniques have been applied to stock (market) prediction. Feature selection, a pre-processing step of data mining, aims at filtering out unrepresentative variables from a given dataset for effective prediction. As using different feature selection methods will lead to different features selected and thus affect the prediction performance, the purpose of this paper is to combine multiple feature selection methods to identify more representative variables for better prediction. In particular, three well-known feature selection methods, which are Principal Component Analysis (PCA), Genetic Algorithms (GA) and decision trees (CART), are used. The combination methods to filter out unrepresentative variables are based on union, intersection, and multi-intersection strategies. For the prediction model, the back-propagation neural network is developed. Experimental results show that the intersection between PCA and GA and the multi-intersection of PCA, GA, and CART perform the best, which are of 79% and 78.98% accuracy respectively. In addition, these two combined feature selection methods filter out near 80% unrepresentative features from 85 original variables, resulting in 14 and 17 important features respectively. These variables are the important factors for stock prediction and can be used for future investment decisions.