A.L. Pomerantsev , S. Kucheryavskiy , O. Ye Rodionova
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引用次数: 0
摘要
用于回归和判别的变量选择方法已经发展得很好。然而,已知的方法并不能充分解决一个类分类器的问题。本研究旨在填补这一空白。结果针对一类分类器,提出了一种新的变量选择方法LOVE (Leave One variable Excluded)。LOVE属于包装器家族,与大多数已知的自动方法不同,它是交互式的。所考虑的四个案例表明,该方法在各种场景下都具有良好的性能。研究表明LOVE可以:(1)增强分类器性能;(2)防止过拟合,提高模型稳定性;(3)修复异常值,但不删除;(4)更好地理解影响决策的因素。
Variable selection for one class classifiers. Introduction of LOVE
Background
Variable selection methods for regression and discrimination are well developed. However, the known methods do not adequately address the problem in the case of one class classifiers. This study aims to fill this gap.
Results
A new variable selection method, LOVE (Leave One Variable Excluded), created specifically for one class classifiers is proposed. LOVE belongs to the wrapper family and is interactive, in contrast to most known methods, which are automatic. The four cases considered demonstrate that the method performs well in various scenarios.
Significance
It is shown that LOVE can: (1) enhance classifier performance; (2) prevent overfitting and improve model stability; (3) fix outliers without deletion; and (4) provide a better understanding of what factors influence the decision.
期刊介绍:
Analytica Chimica Acta has an open access mirror journal Analytica Chimica Acta: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review.
Analytica Chimica Acta provides a forum for the rapid publication of original research, and critical, comprehensive reviews dealing with all aspects of fundamental and applied modern analytical chemistry. The journal welcomes the submission of research papers which report studies concerning the development of new and significant analytical methodologies. In determining the suitability of submitted articles for publication, particular scrutiny will be placed on the degree of novelty and impact of the research and the extent to which it adds to the existing body of knowledge in analytical chemistry.