clustrd
Methods for Joint Dimension Reduction and Clustering
A class of methods that combine dimension reduction and clustering of continuous, categorical or mixed-type data (Markos, Iodice D'Enza and van de Velden 2019; doi:10.18637/jss.v091.i10). For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; doi:10.1016/S0167-9473(00)00064-5) and reduced K-means (De Soete and Carroll 1994; doi:10.1007/978-3-642-51175-2_24); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; doi:10.1007/s11336-004-1173-x), i-FCB (Iodice D'Enza and Palumbo 2013, doi:10.1007/s00180-012-0329-x) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2017; doi:10.1007/s11336-016-9514-0), which combine multiple correspondence analysis with K-means. For mixed-type data, it provides mixed Reduced K-means and mixed Factorial K-means (van de Velden, Iodice D'Enza and Markos 2019; doi:10.1002/wics.1456), which combine PCA for mixed-type data with K-means.
- Version1.4.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release07/16/2022
Team
Angelos Markos
Michel van de Velden
Show author detailsRolesAuthorAlfonso Iodice D'Enza
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 471 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 11 times.
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Last 365 days
This package has been downloaded 6,479 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Jul 16, 2024 with 122 downloads.
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Dependencies
- Depends1 package
- Imports10 packages
- Reverse Suggests2 packages