Journal ArticleDOI
Integrating extended classifier system and knowledge extraction model for financial investment prediction: An empirical study
An-Pin Chen,Mu Yen Chen +1 more
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TLDR
The learning classifier systems (LCS) technique is adopted to provide a three-phase knowledge extraction methodology, which makes continues and instant learning while integrates multiple rule sets into a centralized knowledge base.Abstract:
Machine learning methods such as fuzzy logic, neural networks and decision tree induction have been applied to learn rules, however they can get trapped into a local optimal. Based on the principle of natural evolution and global searching, a genetic algorithm is promising for obtaining better results. This article adopts the learning classifier systems (LCS) technique to provide a three-phase knowledge extraction methodology, which makes continues and instant learning while integrates multiple rule sets into a centralized knowledge base. This paper makes three important contributions: (1) it represents various rule sets that are derived from different sources and encoded as a fixed-length bit string in the knowledge encoding phase; (2) it uses three criteria (accuracy, coverage, and fitness) to select an optimal set of rules from a large population in the knowledge extraction phase; (3) it applies genetic operations to generate optimal rule sets in the knowledge integration phase. The experiments prove that the rule sets derived by the proposed approach is more accurate than other machine learning algorithm.read more
Citations
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Journal ArticleDOI
Constructing a personalized e-learning system based on genetic algorithm and case-based reasoning approach
TL;DR: A genetic-based curriculum sequencing approach that will generate a personalized curriculum sequencing and empirical research is used to indicate that the proposed approach can generate the appropriate course materials for learners, based on individual learner requirements, to help them to learn more effectively in a Web-based environment.
Journal ArticleDOI
A self-adjusting e-course generation process for personalized learning
TL;DR: The investigation results indicate that the proposed self-adjusting e-course generation process adapts to learners by utilizing the feedback from many learners, which support to provide a truly personalized learning environment.
Journal ArticleDOI
Integration of heterogeneous models to predict consumer behavior
Jae Kwon Bae,Jinhwa Kim +1 more
TL;DR: The results from the experiments show that the performance of integrated model is superior to that of all other models such as association rule, frequency matrix, and tree-based models.
Journal ArticleDOI
An evolutionary trend reversion model for stock trading rule discovery
TL;DR: An Evolutionary Trend Reversion Model (eTrendRev), which is based on the proposed XCS with learn mode (XCSL) and trend-reversion strategy, and back-testing results indicate that eTrendRev can produce higher return with lower risk and recognize significant market turning points in a timely fashion.
Journal ArticleDOI
Increasing accuracy of two-class pattern recognition with enhanced fuzzy functions
TL;DR: The experimental results indicate that the new IFCF is a promising method for two-class pattern recognition problems and the information on natural grouping of data samples are utilized as additional predictors of each fuzzy classifier function to improve accuracy of system model.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Book
Expert Systems: Principles and Programming
Joseph C. Giarratano,Gary Riley +1 more
TL;DR: This new edition features a balanced blend of expert systems theory and practice; a detailed presentation of CLIPS Version 6.0, a rule-based programming language for expert systems design; and an IBM PC 3 1/2''.
Journal ArticleDOI
Induction of fuzzy decision trees
Yufei Yuan,Michael J. Shaw +1 more
TL;DR: A fuzzy decision tree induction method, which is based on the reduction of classification ambiguity with fuzzy evidence, is developed, which represents classification knowledge more naturally to the way of human thinking and are more robust in tolerating imprecise, conflict, and missing information.