Installation
About
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. For more information, see Foss, Markatou, Ray, & Heching (2016) doi:10.1007/s10994-016-5575-7 and Foss & Markatou (2018) doi:10.18637/jss.v083.i13.
Citation | kamila citation info |
github.com/ahfoss/kamila | |
Bug report | File report |
Key Metrics
Downloads
Yesterday | 7 0% |
Last 7 days | 63 +34% |
Last 30 days | 307 +2% |
Last 90 days | 814 -27% |
Last 365 days | 4.349 +3% |
Maintainer
Maintainer | Alexander Foss |