clustrd

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.

Last 30 days

This package has been downloaded 457 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 6,416 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.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.