Create a kite-square plot for contingency tables using 'ggplot2', to display their relevant quantities in a single figure (marginal, conditional, expected, observed, chi-squared). The plot resembles a flying kite inside a square if the variables are independent, and deviates from this the more dependence exists.

A wrapper for querying 'WISKI' databases via the 'KiWIS' 'REST' API. 'WISKI' is an 'SQL' relational database 
  used for the collection and storage of water data developed by KISTERS and 'KiWIS' is a 'REST' service that provides
  access to 'WISKI' databases via HTTP requests (<https://www.kisters.eu/water-weather-and-environment/>). 
  Contains a list of default databases (called 'hubs') and also allows users to provide their own 'KiWIS' URL. 
  Supports the entire query process- from metadata to specific time series values. All data is returned as tidy tibbles.

Weighted k-Nearest Neighbors for Classification, Regression
    and Clustering.

A variable selection procedure, dubbed KKO, for nonparametric additive model with finite-sample false discovery rate control guarantee. The method integrates three key components: knockoffs, subsampling for stability, and random feature mapping for nonparametric function approximation. For more information, see the accompanying paper: Dai, X., Lyu, X., & Li, L. (2021). “Kernel Knockoffs Selection for Nonparametric Additive Models”. arXiv preprint <arXiv:2105.11659>.

Miscellaneous functions for classification and visualization,
     e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, 
     an interface to 'svmlight' and stepclass() wrapper variable selection 
     for supervised classification, partimat() visualization of classification rules 
         and shardsplot() of cluster results as well as kmodes() clustering for categorical data, 
     corclust() variable clustering, variable extraction from different variable clustering models 
         and weight of evidence preprocessing.

Functions to search, retrieve, apply and update classifications 
  and codelists using Statistics Norway's API <https://www.ssb.no/klass> 
  from the system 'KLASS'. Retrieves classifications by date with options 
  to choose language, hierarchical level and formatting.