R package kamila. Implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Amiri, Leila; Khazaei, Mojtaba; Ganjali, Mojtaba: Mixtures of general location model with factor analyzer covariance structure for clustering mixed type data (2019)
- D’Urso, Pierpaolo; Massari, Riccardo: Fuzzy clustering of mixed data (2019)
- Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018) not zbMATH