Retraction Note: Subject choice in educational data sets by using principal component and procrustes analysis

Ansar Khan; Mrityunjoy Jana; Subhankar Bera; Arosikha Das

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Retraction Note: Subject choice in educational data sets by using principal component and procrustes analysis

机译：收缩注意：通过使用主成分和促进教育数据集中的主题选择和促进分析

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The authors are retracting this article (Khan et al., 2016) because it overlaps with a previously published article (Siswadi et al., 2012). All authors agree with this retraction.

机译：作者正在撤回本文（Khan等，2016），因为它与先前发表的文章重叠（Siswadi等，2012）。所有作者都同意此撤回。

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来源
《Modeling Earth Systems and Environment》 |2018年第4期|共1页
作者
Ansar Khan; Mrityunjoy Jana; Subhankar Bera; Arosikha Das;
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作者单位

Department of Geography and Environment Management Vidyasagar University;

Department of Education North Orissa University;

Department of Geography and Environment Management Vidyasagar University;

Department of Applied Geography Ravenshaw University;

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原文格式 PDF
正文语种 eng
中图分类环境科学、安全科学;
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入库时间 2022-08-20 04:08:34

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1. Retraction Note: Subject choice in educational data sets by using principal component and procrustes analysis [J] . Ansar Khan, Mrityunjoy Jana, Subhankar Bera, Modeling Earth Systems and Environment . 2018,第4期

机译：收缩注意：通过使用主成分和促进教育数据集中的主题选择和促进分析
2. PM₁₀ and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set [J] . Pierina Ielpo, Vincenzo Paolillo, Gianluigi de Gennaro, Chemistry central journal . 2014,第1期

机译：来自巴里省空气质量监测网络的PM _{10 和气态污染物趋势：两年半数据集的主成分分析和绝对主成分评分}
3. PM 10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set [J] . Pierina Ielpo, Vincenzo Paolillo, Gianluigi de Gennaro, Chemistry central journal . 2014,第1期

机译：来自巴里省空气质量监测网络的PM 10和气态污染物趋势：两年半数据集的主成分分析和绝对主成分评分
4. Note on the use of Principal Component Analysis (PCA) and clustering for the analysis of wafer level ATPG data [C] . Kartik Ramanujachar, Satish Draksharam, ASM International International Symposium for Testing and Failure Analysis . 2006

机译：关于使用主成分分析（PCA）和聚类用于分析晶圆级ATPG数据的群集
5. Using principal component analysis (PCA) to obtain auxiliary variables for missing data in large data sets. [D] . Howard, Waylon J. 2012

机译：使用主成分分析（PCA）获得大数据集中缺失数据的辅助变量。
6. SPSS Syntax for Combining Results of Principal Component Analysis of Multiply Imputed Data Sets using Generalized Procrustes Analysis [O] . Bart van Wingerde, Joost van Ginkel 2021

机译：SPSS语法用于使用广义促进数据集的主要分支数据集的主要成分分析结果
7. PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set [O] . Pierina Ielpo, Vincenzo Paolillo, Gianluigi de Gennaro, 2014

机译：来自巴里省空气质量监测网络的PM10和气态污染物趋势：基于两年半数据集的主成分分析和绝对主成分评分

Retraction Note: Subject choice in educational data sets by using principal component and procrustes analysis

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