Enhancing Explainable Machine Learning by Reconsidering Initially Unselected Items in Feature Selection for Classification
Feature selection is a common step in data preprocessing that precedes machine learning to reduce data space and the computational cost of processing or obtaining the data. Filtering out uninformative variables is also important for knowledge discovery. By reducing the data space to only those compo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
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| Series: | BioMedInformatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7426/2/4/47 |