Feature selection methods for financial engineering
I experiment with a well-recognized filter-wrapper hybrid feature selection method – minimal-Redundancy-Maximal-Relevance Criterion feature selection refined by a wrapper using Support Vector Machines. I apply this hybrid method to predict the stock trend on 10 indexes on Singapore’s own...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2014
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| Online Access: | http://hdl.handle.net/10356/60500 |