Stability of feature selection algorithm: A review

National Institute of Technology Nagaland

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Abstract

Feature selection technique is a knowledge discovery tool which provides an understanding of the problem through the analysis of the most relevant features. Feature selection aims at building better classifier by listing significant features which also helps in reducing computational overload. Due to existing high throughput technologies and their recent advancements are resulting in high dimensional data due to which feature selection is being treated as handy and mandatory in such datasets. This actually questions the interpretability and stability of traditional feature selection algorithms. The high correlation in features frequently produces multiple equally optimal signatures, which makes traditional…

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606
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Authors

2

Topics & keywords

Keywords
  • Feature selection
  • Interpretability
  • Minimum redundancy feature selection
  • Computer science
  • Classifier (UML)
  • Data mining
  • Feature (linguistics)
  • Artificial intelligence
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