{rfName}
sc

Indexed in

License and use

Citations

4

Altmetrics

Analysis of institutional authors

Ramos-Carreño CCorresponding AuthorTorrecilla JlAuthorSuarez AAuthor

Share

Publications
>
Proceedings Paper

scikit-fda: Computational Tools for Machine Learning with Functional Data

Publicated to:Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. 2022-October 213-218 - 2022-01-01 2022-October(), DOI: 10.1109/ICTAI56018.2022.00038

Authors: Ramos-Carreno, Carlos; Luis Torrecilla, Jose; Hong, Yujian; Suarez, Alberto

Affiliations

Univ Autonoma Madrid, Dept Comp Sci, Madrid, Spain - Author
Univ Autonoma Madrid, Dept Math, Madrid, Spain - Author
Universidad Autónoma de Madrid - Author

Abstract

Machine learning from functional data poses particular challenges that require specific computational tools that take into account their structure. In this work, we present scikit-fda, a Python library for functional data analysis, visualization, preprocessing, and machine learning. The library is designed for smooth integration in the Python scientific ecosystem. In particular, it complements and can be used in combination with scikit-learn, the reference Python library for machine learning. The functionality of scikit-fda is illustrated in clustering, regression, and classification problems from different areas of application.

Keywords

data visualizationmachine learningpython toolboxData visualizationFunctional data analysisMachine learningPython toolbox

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

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: 1.23, 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 Jun 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-06-23, the following number of citations:

  • WoS: 2
  • Scopus: 2

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 2025-06-23:

  • 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: 5 (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.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://repositorio.uam.es/handle/10486/711587

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 (RAMOS CARREÑO, CARLOS) and Last Author (SUAREZ GONZALEZ, ALBERTO).

the author responsible for correspondence tasks has been RAMOS CARREÑO, CARLOS.