【摘要】 研究了基于隐含信息的半监督学习方法,并将该方法应用于支持向量机和随机森林模型。利用UCI数据库中的数据验证了基于此方法的支持向量机和随机森林的精度。在此基础上,将此种方法应用于肺音识别领域,利用实际的肺音数据对此方法处理实际问题的效果进行了验证,同时实验分析了无标记样本的数量以及质量对此方法的影响。更多还原

【Abstract】 Implicit information semi supervised learning algorithm was studied. The implicit information semi supervised learning algorithm was used in support vector machine and random forest, which were called semi-SVM and semi-RF. The semi-SVM and semi-RF were evaluated by using UCI, the experimental results show that the semi-SVM and semi-RF are more effective and more precise. The semi-SVM and semi-RF were applied to classifying lung sounds, and verified the effect by using the actual lung sounds data. the quantity and quality of samples affect semi-SVM and semi-RF were analyzed.更多还原