| Chapter title | A machine learning investigation of a beta-carotenoid dataset |
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| Authors | Revett, K. |
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| Editors | Bello, R., Falcón, R., Pedrycz, W. and Kacprzyk, J. |
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| Abstract | Numerous reports have implicated a diet and/or conditions where levels of carotene/retinol are below minimal daily requirements may pre-dispose individuals to an increased susceptibility to various types of cancer. This study investigates dietary and other factors that may influence plasma levels of these anti-oxidants. A rough sets approach is employed on a clinical dataset to determine the attributes and their values are associated with plamsa levels of carotene/retinol. The resulting classifier produced an accuracy of approximately 90% for both beta-carotene and retinol. The results from this study indicate that age, smoking, and dietary intake of these endogenous anti-oxidants is predictive of plasma levels. |
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| Book title | Granular computing: at the junction of rough sets and fuzzy sets |
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| Year | 2008 |
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| Publisher | Springer |
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| Publication dates |
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| Published | 2008 |
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| Place of publication | Berlin / Heidelberg |
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| Series | Studies in fuzziness and soft computing |
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| ISBN | 9783540769729 |
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| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-540-76973-6_14 |
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| Journal citation | (224), pp. 211-227 |
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