What is it about?
Each dataset consists of multiple features. Selection of features for improving the system's performance is important for any system. In this paper, we covered various methods of feature selection. It includes filter method, wrapper method and hybrid method with their advantages and disadvantages.
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Why is it important?
Not all features are important of systems performance. For example, if the dataset is of payroll system for any organization and it contains features like age, gender, city, post etc. Then increment in salary mostly depends on post and experience. it does not depend on age or gender or city. So, these features are not important, and it could be removed from the dataset. sometimes, such features decrease the system performance. So, removal of these features is important.
Perspectives
As this article covers all the details including advantages and disadvantages of different methods of feature selection. So, in my opinion, this paper will be beneficial for researchers doing research in this field.
Mr. Ankur Kumar
Shri Ram Murti Smarak College of Engineering, Technology and Research
Read the Original
This page is a summary of: Literature Review on Development of Feature Selection and Learning
Mechanism for Fuzzy Rule-Based System, Recent Advances in Computer Science and Communications, May 2023, Bentham Science Publishers,
DOI: 10.2174/2666255816666220823163913.
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