e1071 (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to e1071 (R package) (https://CRAN.R-project.org/package=e1071), 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#

26 papers in the tracked journals link to e1071 (R package) in their Crossref records, the first in 2016; most of them (6) in 2018.
By category: AI (12), Finance (4) and Operations Research (4); the journals with the most are Expert Systems with Applications (4), Financial Innovation (3) and Machine Learning (2).
2 of the papers build on one another: a later paper cites an earlier one that also links e1071 (R package).

By year#

20162026

Papers linking to e1071 (R package) by publication year
Year	Papers
2016	1
2017	1
2018	6
2019	5
2020	1
2021	2
2022	2
2023	1
2024	3
2025	2
2026	2

Journals#

Journals whose papers link to e1071 (R package) most
Journal	Papers
Expert Systems with Applications	4
Financial Innovation	3
Machine Learning	2
Transportation Research Part C Emerging Technologies	2
Pattern Recognition	2

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Instance spaces for machine learning classification Machine Learning, 2017
- On normalization and algorithm selection for unsupervised outlier detection Data Mining and Knowledge Discovery, 2019 — cites the paper above

Papers linking to e1071 (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2021-01-06	Forecasting and trading cryptocurrencies with machine learning under changing market conditions	Financial Innovation	Hélder Sebastião, Pedro Manuel Cortesão Godinho	241	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
2018-11-02	Marketing analytics: Methods, practice, implementation, and links to other fields	Expert Systems with Applications	Stephen L. France, Sanjoy Ghose	107	cites it
2018-01-01	Machine Learning and Sampling Scheme: An Empirical Study of Money Laundering Detection	Computational Economics	Yan Zhang, Peter Trubey	102	cites it
2018-09-27	A Bayesian dynamic updating approach for urban expressway real-time crash risk evaluation	Transportation Research Part C Emerging Technologies	Kui Yang, Xuesong Wang, Rongjie Yu	89	cites it
2019-11-21	On normalization and algorithm selection for unsupervised outlier detection	Data Mining and Knowledge Discovery	Sevvandi Kandanaarachchi, Mario Andrés Muñoz, Rob J. Hyndman et al.	62	cites it
2021-03-10	Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany	Business & Information Systems Engineering	Simon Wenninger, Christian Wiethe	47	cites it
2018-12-10	Piecewise regression analysis through information criteria using mathematical programming	Expert Systems with Applications	Ioannis Gkioulekas, Lazaros G. Papageorgiou	45	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
2022-05-13	Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?	The North American Journal of Economics and Finance	Perry Sadorsky	39	cites it
2018-05-16	Real time location prediction with taxi-GPS data streams	Transportation Research Part C Emerging Technologies	Arnab Kumar Laha, Sayan Putatunda	37	cites it
2016-10-17	An ensemble of ordered logistic regression and random forest for child garment size matching	Computers & Industrial Engineering	Ana Piérola, Irene Epifanio, Sandra Alemany	36	cites it
2020-02-01	Statistical learning and exchange rate forecasting	International Journal of Forecasting	Emilio Colombo, Matteo Maria Pelagatti	33	cites it
2019-07-11	A hybrid Bayesian-network proposition for forecasting the crude oil price	Financial Innovation	Babak Fazelabdolabadi	30	cites it
2024-03-01	Examining user behavior with machine learning for effective mobile peer-to-peer payment adoption	Financial Innovation	Blanco-Oliver Antonio, Lara-Rubio Juan, Irimia-Diéguez Ana et al.	29	cites it
2018-12-05	Improved model-based clustering performance using Bayesian initialization averaging	Computational Statistics	Adrian R. O’Hagan, Arthur White	26	cites it
2019-06-22	Recognising innovative companies by using a diversified stacked generalisation method for website classification	Applied Intelligence	Marcin Mirończuk, Jarosław Protasiewicz	7	cites it
2019-02-20	Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series	Data Mining and Knowledge Discovery	Rebecca Wilson, Idris Arthur Eckley, Matthew A. Nunes et al.	6	cites it
2019-10-05	Ensemble quantile classifier	Computational Statistics & Data Analysis	Yuanhao Lai, Ian McLeod	5	cites it
2022-04-01	Is the vessel fishing? Discrimination of fishing activity with low-cost intelligent mobile devices through traditional and heuristic approaches	Expert Systems with Applications	M. M. Galotto-Tebar, A. Pomares-Padilla, Ivone A. Czerwinski et al.	4	cites it
2025-07-28	Machine learning-driven insights for business innovation: Analyzing financial performance in Vietnam’s emerging economy 2010–2024	Journal of Open Innovation Technology Market and Complexity	Phạm Trung Hiếu, Thi Hang, Doan Huynh Thu Hoai et al.	2	cites it
2025-08-22	Spindle thermal error modeling with linear and nonlinear hybrid tandem metamodel based on statistical and machine learning approaches	Expert Systems with Applications	Menghua Li, Mingchang Chih, Chia-Fu Kou et al.	2	cites it
2024-04-14	Prediction of annual rice imports emphasizes on systematic error reduction with smoothing series and optimal parameter selection techniques	Neural Computing and Applications	Thoranin Sujjaviriyasup	1	cites it
2024-07-09	Permutation-invariant linear classifiers	Machine Learning	Ludwig M. Lausser, Robin Szekely, Hans Armin Kestler	1	cites it
2026-03-21	Linear complexity hyperparameter tuning of the quadratic kernel for support vector classification	Pattern Recognition	Manuel Fernández-Delgado, A.L. Pereira-Costa, Eva Cernadas	0	cites it
2026-04-16	Simulation and Analysis of Multifractional Stochastic Processes with R Package Rmfrac	Methodology And Computing In Applied Probability	Andriy Ya. Olenko, Nemini Samarakoon	0	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). e1071 (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-e1071

@misc{scholar4ai-code-cran-e1071,
  author = {{Scholar4AI}},
  title = {e1071 (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-e1071}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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