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Impact on the Sustainable Development Goals (SDGs)

Analysis of institutional authors

Gomez DCorresponding Author

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June 17, 2024
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An Empirical Overview of the No Free Lunch Theorem and Its Effect on Real-World Machine Learning Classification.

Publicated to:Neural Computation. 28 (1): 216-228 - 2016-01-01 28(1), DOI: 10.1162/neco_a_00793

Authors: Gómez D; Rojas A

Affiliations

Telematics Engineering Department, Polytechnical University of Catalonia, Barcelona 08034, Spain alfonso@entel.upc.edu. - Author
Telematics Engineering Department, Polytechnical University of Catalonia, Barcelona 08034, Spain david.gomez.guillen@entel.upc.edu. - Author

Abstract

A sizable amount of research has been done to improve the mechanisms for knowledge extraction such as machine learning classification or regression. Quite unintuitively, the no free lunch (NFL) theorem states that all optimization problem strategies perform equally well when averaged over all possible problems. This fact seems to clash with the effort put forth toward better algorithms. This letter explores empirically the effect of the NFL theorem on some popular machine learning classification techniques over real-world data sets.

Keywords

Quality education

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Neural Computation due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2016, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Arts and Humanities (Miscellaneous).

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 21.76, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-17, the following number of citations:

  • Europe PMC: 26
  • Open Alex: 90

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-17:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 76 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
Continuing with the social impact of the work, it is important to emphasize that, due to its content, it can be assigned to the area of interest of ODS 4 - Quality Education, with a probability of 54% according to the mBERT algorithm developed by Aurora University.

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Gomez Guillen, David) .

the author responsible for correspondence tasks has been Gomez Guillen, David.