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稳定准确的特征选择

Stable and Accurate Feature Selection
课程网址: http://videolectures.net/ecmlpkdd09_cataltepe_safs/  
主讲教师: Zehra Cataltepe
开课单位: 伊斯坦布尔技术大学
开课时间: 2009-10-20
课程语种: 英语
中文简介:
除了准确性之外,稳定性也是特征选择算法成功的衡量标准。当数据集中的样本数量很少且维度很高时,稳定性尤其令人担忧。在本研究中,我们引入稳定性测量,并对不同数据集上的MRMR(最小冗余最大相关性)特征选择算法执行精度和稳定性测量。 MRMR,MID(互信息差异)和$ MIQ $(互信息商数)使用的两个特征评估标准导致类似的准确性,但MID更稳定。我们还引入了一个新的特征选择标准MIDalpha,其中所选特征的冗余和相关性由参数α控制。
课程简介: In addition to accuracy, stability is also a measure of success for a feature selection algorithm. Stability could especially be a concern when the number of samples in a data set is small and the dimensionality is high. In this study, we introduce a stability measure, and perform both accuracy and stability measurements of MRMR (Minimum Redundancy Maximum Relevance) feature selection algorithm on different data sets. The two feature evaluation criteria used by MRMR, MID (Mutual Information Difference) and $MIQ$ (Mutual Information Quotient), result in similar accuracies, but MID is more stable. We also introduce a new feature selection criterion, MIDalpha, where redundancy and relevance of selected features are controlled by parameter alpha.
关 键 词: 准确性; 稳定性; 算法成功
课程来源: 视频讲座网
最后编审: 2019-03-24:cwx
阅读次数: 50