Feature Selection: A Data Perspective
Arizona State University · Michigan State University
Abstract
Feature selection, as a data preprocessing strategy, has been proven to be effective and efficient in preparing data (especially high-dimensional data) for various data mining and machine learning problems. The objectives of feature selection include: building simpler and more comprehensible models, improving data mining performance, and preparing clean, understandable data. The recent proliferation of big data has presented some substantial challenges and opportunities to feature selection. In this survey, we provide a comprehensive and structured overview of recent advances in feature selection research. Motivated by current challenges and opportunities in the era of big data, we revisit feature selection…
Citation impact
- FWCI
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- References
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Authors
7Topics & keywords
- Feature selection
- Computer science
- Data pre-processing
- Feature (linguistics)
- Big data
- Selection (genetic algorithm)
- Data mining
- Minimum redundancy feature selection
- Industry, innovation and infrastructure