Investigators at National Center for Biotechnology Information Target Machine Learning - Support Vector Machines

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Investigators at National Center for Biotechnology Information Target Machine Learning - Support Vector Machines

机译：国家生物技术信息目标机器学习中心的研究人员-支持向量机

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2011 APR 18 - (VerticalNews.com) -- New investigation results, 'Binaryrnclassification of aqueous solubility using support vector machines with reduction andrnrecombination feature selection,' are detailed in a study published in Journal of ChemicalrnInformation and Modeling. "Aqueous solubility is recognized as a critical parameter in both thernearly-and late-stage drug discovery. Therefore, in silico modeling of solubility has attractedrnextensive interests in recent years," researchers in Bethesda, United States report.

机译：2011年4月18日-（VerticalNews.com）-发表在Journal of ChemicalInformation and Modeling上的一项研究中详细介绍了新的调查结果，“使用支持向量机通过还原和重组特征选择对水溶性进行二元分类”。美国贝塞斯达的研究人员称：“水溶性在近代和晚期药物开发中均被视为关键参数。因此，近年来对溶解度进行计算机模拟已经引起了广泛的关注。”

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《Energy Business Journal》 |2011年第31期|30-31|共2页
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City:Bethesda; State:Maryland; Country:United States; Emerging Technologies; Machine Learning; Machine Learning - Support Vector Machines; Support Vector Machines;

机译：城市：贝塞斯达;州：马里兰州;国家：美国;新兴技术;机器学习;机器学习-支持向量机;支持向量机;

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Investigators at National Center for Biotechnology Information Target Machine Learning - Support Vector Machines

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