kknn (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to kknn (R package) (https://CRAN.R-project.org/package=kknn), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

4 papers in the tracked journals link to kknn (R package) in their Crossref records, the first in 2017; most of them (1) in 2023.
By category: AI (3) and Statistics (1); the journals with the most are Computational Statistics (1), Information Fusion (1) and Machine Learning (1).

By year#

20172023

Papers linking to kknn (R package) by publication year
Year	Papers
2017	1
2019	1
2022	1
2023	1

Journals#

Journals whose papers link to kknn (R package) most
Journal	Papers
Computational Statistics	1
Information Fusion	1
Machine Learning	1
Pattern Recognition	1

Papers linking to kknn (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2022-03-04	Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features	Computational Statistics	Florian Pargent, Florian Pfisterer, Janek Thomas et al.	171	cites it
2017-12-28	Instance spaces for machine learning classification	Machine Learning	Mario Andrés Muñoz, Laura Villanova, Davaatseren Baatar et al.	153	cites it
2023-05-01	A k nearest neighbour ensemble via extended neighbourhood rule and feature subsets	Pattern Recognition	Amjad Ali, Muhammad Hamraz, Naz Gul et al.	44	cites it
2019-07-18	Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines	Information Fusion	Francisco J. Pulgar, Francisco Charte, Antonio J. Rivera et al.	43	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). kknn (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-kknn

@misc{scholar4ai-code-cran-kknn,
  author = {{Scholar4AI}},
  title = {kknn (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-kknn}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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