Maximum Homogeneity Clustering for Univariate Data

Maximum homogeneity clustering algorithm for one-dimensional data described in W. D. Fisher (1958) via dynamic programming.

oneclust

Implements the maximum homogeneity clustering algorithm for one-dimensional data described in W. D. Fisher (1958) <doi:10.1080/01621459.1958.10501479> via dynamic programming.

Check vignette("oneclust") for its applications in feature engineering, regression modeling, and peak calling.

Installation

You can install oneclust from CRAN:

install.packages("oneclust")

Or try the development version from GitHub:

remotes::install_github("nanxstats/oneclust")

Gallery

Feature engineering for high-cardinality categorical features

Grouping coefficients in regression models

Sequential data peak calling and segmentation

License

oneclust is free and open source software, licensed under GPL-3.