# OPTICS K-Xi Density-Based Clustering

## Documentation for package ‘opticskxi’ version 1.2.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

%$% | Exposition pipe
%<>% | Assignment pipe
%>% | Pipe
contingency_table | Contingency table
cosine_simi | Cosine similarity between vectors and/or matrices.
crohn | Crohn's disease data
dist_matrix | dist_matrix
ensemble_metrics | Compute ensemble metrics
ensemble_metrics_bootstrap | Select models based on ensemble metrics
ensemble_models | Select best models based on ensemble metrics
fortify_dimred | Fortify a dimension reduction object
fortify_ica | Get and fortify ICA
fortify_pca | Get and fortify PCA
get_best_kxi | Get best k-Xi model
ggpairs | Plot multiple axes of a data frame or a fortified dimension reduction.
ggplot_kxi_metrics | Ggplot OPTICS k-Xi metrics
ggplot_optics | Ggplot optics
gtable_kxi_profiles | Gtable OPTICS k-Xi distance profiles
hla | The HLA data
multishapes | A dataset containing clusters of multiple shapes
m_psych_embeds | A dataset containing the embeddings matrix of psychological related words
nice_palette | Nice palette
normalize | Matrix normalization
norm_inprod | norm_inprod
opticskxi | OPTICS k-Xi clustering algorithm
opticskxi_pipeline | OPTICS k-Xi models comparison pipeline
print_vignette_table | Print vignette table
residuals_table | Residuals table
stddev_mean | stddev_mean