...信息学数据库以及相关文献中找到相 关的实验数据，构建样本训练集和预测集，并采用支持向量分类器（support vector classifier，SVC）方法求解；最终，建立了蛋白酶体酶切内源性抗原的理论预测模型，并 得到了蛋白酶体酶切内源性抗原的特异性...
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在此基础上，研究了用球结构支持向量机作分类器，对滚动轴承内圈故障的劣化程度进行识别的理论和方法。
Basing on these, study theory and method of using Sphere-structured Support Vector Machines to recognize the roll bearing inside track's fault deterioration extent.
为了将一般增量学习算法扩展到并行计算环境中，提出一种基于多支持向量机分类器的增量学习算法。
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed.
支持向量机分类器克服了当前常用的模式识别方法的缺点，有效提高了识别率。
Support vector machine classifier overcome the shortcoming of the present and commonly used pattern-recognition methods, and has improved the recognition rate effectively.
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