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About A Review of Feature Selection Techniques in Bioinformatics
This document reviews feature selection techniques that have become important in many bioinformatics applications due to the large number of features/variables involved. It provides a basic taxonomy of feature selection techniques, categorizing them as filter, wrapper or embedded methods. Filter methods evaluate features based on univariate statistical tests without involving machine learning algorithms, while wrapper and embedded methods evaluate feature subsets using machine learning algorithms. The review discusses advantages and disadvantages of different techniques and their applications in bioinformatics for improving model performance and gaining biological insights.
Detailed Information
| Author: | ['John Doe'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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