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Identifying Corporate Performance Factors Based on Feature Selection in Statistical Pattern Recognition: METHODS, APPLICATION, INTERPRETATION

机译:基于特征选择的统计模式识别中的企业绩效因素识别:方法,应用,解释

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摘要

This publication summarizes and extends methodology of feature selection (FS) and pattern recognition in search for competitiveness factors and methodology of corporate financial performance (CFP) measurement. Several methods were evaluated and Dependency-Aware Feature Ranking combined with non-linear regression model were applied. Also, this publication suggests and verifies methodology of interpretation results of the FS methods. For start was employed multidimensional linear regression, succeeded by clustering companies according to the factors identified by FS into homogenous groups, dividing them into quartiles based on their CFP and identifying similar values of the factors. This way was captured the non-linearity in the data.
机译:该出版物总结并扩展了特征选择(FS)和模式识别的方法,以寻找竞争因素和公司财务绩效(CFP)度量方法。对几种方法进行了评估,并应用了依赖感知的特征等级与非线性回归模型相结合。另外,该出版物建议并验证了FS方法的解释结果的方法。首先使用多维线性回归,然后由公司根据FS识别的因素将其聚类为同类,然后根据其CFP将其分为四分位数,并确定相似的值。这样就捕获了数据中的非线性。

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