论文标题
MATLAB工具箱，用于功能重要性排名
A Matlab Toolbox for Feature Importance Ranking
论文作者
论文摘要
更加关注功能重要性排名（FIR），特别是当可以提取数千个功能以进行智能诊断和个性化医学时。已经提出了大量的FIR方法，而很少有用于比较和现实生活的应用。在这项研究中，提出了MATLAB工具箱，并收集了30个算法。此外，在163张超声图像的数据库上评估了该工具箱。对于每个乳房肿块病变，提取15个特征。为了找出分类特征的最佳子集，对特征的所有组合进行了测试，并将线性支持向量机用于超声图像中注释的病变的恶性预测。最后，根据性能比较分析了FIR的有效性。该工具箱在线（https://github.com/nicoyucn/matfir）。在我们未来的工作中，将集成更多的FIR方法，功能选择方法和机器学习分类器。
More attention is being paid for feature importance ranking (FIR), in particular when thousands of features can be extracted for intelligent diagnosis and personalized medicine. A large number of FIR approaches have been proposed, while few are integrated for comparison and real-life applications. In this study, a matlab toolbox is presented and a total of 30 algorithms are collected. Moreover, the toolbox is evaluated on a database of 163 ultrasound images. To each breast mass lesion, 15 features are extracted. To figure out the optimal subset of features for classification, all combinations of features are tested and linear support vector machine is used for the malignancy prediction of lesions annotated in ultrasound images. At last, the effectiveness of FIR is analyzed according to performance comparison. The toolbox is online (https://github.com/NicoYuCN/matFIR). In our future work, more FIR methods, feature selection methods and machine learning classifiers will be integrated.
