Paja, W. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges. Entropy2023, 25, 1223.
Paja, W. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges. Entropy 2023, 25, 1223.
Paja, W. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges. Entropy2023, 25, 1223.
Paja, W. Application of the Fuzzy Approach for Evaluating and Selecting Relevant Objects, Features, and Their Ranges. Entropy 2023, 25, 1223.
Abstract
Significant attribute selection in machine learning is one of the key aspects aimed at simplifying the problem and reducing its dimensionality, and consequently speeding up computation. This paper proposes new algorithms for selecting not only relevant features but also for evaluating and selecting a subset of relevant objects in a dataset. Both algorithms are mainly based on the use of a fuzzy approach. The research presented here yielded preliminary results of a new approach to the problem of selecting relevant attributes and objects, and, in fact, to selecting appropriate ranges of their values. Detailed results obtained on the Sonar dataset show the positive effects of this approach. Moreover, the observed results may suggest the effectiveness of the proposed method in terms of identifying a subset of truly relevant attributes from among those identified by traditional feature selection methods.
Keywords
Attribute and Object Selection; Fuzzification; Discretization
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
