Importance Analysis in the Evaluation of Input Attributes of Classifiers
Elena N. Zaitseva, Vitaly Levashenko, Sergey A. Stankevich · 2023
Most often, the techniques of Machine learning are used for the decision of problems in Reliability Analysis.In this study, we propose to consider the application of the Reliability Analysis based method application for the decision problem in Machine Learning, in particular, the analysis of the influence of input attributes on the classification result.Some attributes are most important for the classification because they significantly influence the classification result than others.A new method for the determination of the most important attributes is proposed.This method is developed based on the approach of Importance Analysis, which is widely used in Reliability Analysis.The attribute's importance is evaluated by structural importance.