Survey of feature selection and extraction techniques for stock market prediction
Survey of feature selection and extraction techniques for stock market prediction
About this item
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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Scope and Contents
Contents
In stock market forecasting, the identification of critical features that affect the performance of machine learning (ML) models is crucial to achieve accurate stock price predictions. Several review papers in the literature have focused on various ML, statistical, and deep learning-based methods used in stock market forecasting. However, no survey...
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Full title
Survey of feature selection and extraction techniques for stock market prediction
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TN_cdi_doaj_primary_oai_doaj_org_article_5fec26d2e196475ca5110ca1a65f7c70
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_5fec26d2e196475ca5110ca1a65f7c70
Other Identifiers
ISSN
2199-4730
E-ISSN
2199-4730
DOI
10.1186/s40854-022-00441-7
