Innovative feature selection methods for bioinformatics
Feature selection has become the focus of much research in areas of application for which datasets with hundreds of thousands of variables are available. These areas include statistics, pattern recognition, machine learning, and knowledge discovery, gene expression array analysis, and combinatorial...
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Format: | Final Year Project |
Language: | English |
Published: |
2012
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Online Access: | http://hdl.handle.net/10356/50246 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Feature selection has become the focus of much research in areas of application for which datasets with hundreds of thousands of variables are available. These areas include statistics, pattern recognition, machine learning, and knowledge discovery, gene expression array analysis, and combinatorial chemistry. With feature selection, we can improve the prediction performance of the predictors, provide faster and more cost-effective predictors, and provide a better understanding of the underlying process that generated data. |
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