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For:
Nandy D
, Chiaromonte F, Li R.
Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems.
J Am Stat Assoc
2022;
117
:1516-1529. [PMID:
36172297
PMCID:
PMC9512254
DOI:
10.1080/01621459.2020.1864380
]
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Citation(s) in
RCA
: 4
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Impact Index Per Article: 2.0
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[Indexed: 01/03/2023]
Number
Cited by Other Article(s)
1
Zhao S
, Fu G. Distribution-free and model-free multivariate feature screening via multivariate rank distance correlation.
J MULTIVARIATE ANAL
2022. [DOI:
10.1016/j.jmva.2022.105081
]
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Citation(s) in
RCA
: 0
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Impact Index Per Article: 0
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[Indexed: 11/27/2022]
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2
Statistical Methods with Applications in Data Mining: A Review of the Most Recent Works.
MATHEMATICS
2022. [DOI:
10.3390/math10060993
]
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Citation(s) in
RCA
: 2
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Impact Index Per Article: 1.0
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[Indexed: 12/04/2022]
Abstract
The importance of statistical methods in finding patterns and trends in otherwise unstructured and complex large sets of data has grown over the past decade, as the amount of data produced keeps growing exponentially and knowledge obtained from understanding data allows to make quick and informed decisions that save time and provide a competitive advantage. For this reason, we have seen considerable advances over the past few years in statistical methods in data mining. This paper is a comprehensive and systematic review of these recent developments in the area of data mining.
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