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Multiple correspondence analysis

Known as: MCA 
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent… 
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Related topics

Related topics

7 relations
Cluster analysisCorrespondence analysisFactor analysisFactor analysis of mixed data

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Organizational practices for learning with work accidents throughout their information cycle
Review
2017
Review
2017
Multiple Correspondence Analysis and its applications
Correspondence analysis (CA) is a statistical visualization method for picturing the association between the levels of… 
2014
2014
Multiple Correspondence Analysis
Multiple correspondence analysis (MCA) is a method of analyse des donnees used to describe, explore, summarize, and visualize… 
2010
2010
FUZZY CLUSTER MULTIPLE CORRESPONDENCE ANALYSIS
Multiple correspondence analysis (MCA) is a useful tool for exploring the interdependencies among multiple-choice variables… 
2010
2010
Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables
We present an alternative approach to Multiple Correspondence Analysis (MCA) that is appropriate when the data consist of ordered… 
Review
2008
Review
2008
Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data
2007
2007
A Multiple Correspondence Analysis to Organize Data Cubes
On Line Analytical Processing (OLAP) is a technology basically created to provide users with tools in order to explore and… 
Highly Cited
2001
Highly Cited
2001
Characterising objective profiles of Costa Rican dairy farmers
Highly Cited
1992
Highly Cited
1992
Interpreting multiple correspondence analysis as a multidimensional scaling method
We formulate multiple correspondence analysis (MCA) as a nonlinear multivariate analysis method that integrates ideas from… 
1983
1983
Correspondence analysis, with an extension towards nominal time series
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