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Syst."],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>As basic research, it has also received increasing attention from people that the \u201ccurse of dimensionality\u201d will lead to increase the cost of data storage and computing; it also influences the efficiency and accuracy of dealing with problems. Feature dimensionality reduction as a key link in the process of pattern recognition has become one hot and difficulty spot in the field of pattern recognition, machine learning and data mining. It is one of the most challenging research fields, which has been favored by most of the scholars\u2019 attention. How to implement \u201clow loss\u201d in the process of feature dimension reduction, keep the nature of the original data, find out the best mapping and get the optimal low dimensional data are the keys aims of the research. In this paper, two-dimensionality reduction methods, feature selection and feature extraction, are introduced; the current mainstream dimensionality reduction algorithms are analyzed, including the method for small sample and method based on deep learning. For each algorithm, examples of their application are given and the advantages and disadvantages of these methods are evaluated.<\/jats:p>","DOI":"10.1007\/s40747-021-00637-x","type":"journal-article","created":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T05:31:54Z","timestamp":1642743114000},"page":"2663-2693","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":648,"title":["Feature dimensionality reduction: a review"],"prefix":"10.1007","volume":"8","author":[{"given":"Weikuan","family":"Jia","sequence":"first","affiliation":[]},{"given":"Meili","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Lian","sequence":"additional","affiliation":[]},{"given":"Sujuan","family":"Hou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,21]]},"reference":[{"issue":"1","key":"637_CR1","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/TIT.1968.1054102","volume":"14","author":"G Hughes","year":"1968","unstructured":"Hughes G (1968) On the mean accuracy of statistical pattern recognizers. 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