mlsanityData to 14 Oct 2026

scikit-fda: A Python Package for Functional Data Analysis

arXiv 2211.02566 ↗First posted 4 Nov 2022stat.CO cs.LG cs.MScited by 12

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Abstract (arXiv)

The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated in Python's scientific ecosystem. In particular, it conforms to the scikit-learn application programming interface so as to take advantage of the functionality for machine learning provided by this package: pipelines, model selection, and hyperparameter tuning, among others. The scikit-fda package has been released as free and open-source software under a 3-Clause BSD license and is open to contributions from the FDA community. The library's extensive documentation includes step-by-step tutorials and detailed examples of use.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 12 of its 102 references that are in the map. First posted on arXiv 4 Nov 2022.

Builds on

12 of 102 references.

References · 12

  1. 2018The UCR Time Series Archivecited by 431
  2. 2018The UEA multivariate time series classification archive, 2018cited by 338
  3. 2020Functional linear regression with truncated signaturescited by 6
  4. 2015The mRMR variable selection method: a comparative study for functional datacited by 5
  5. 2017Multivariate Functional Data Visualization and Outlier Detectioncited by 5
  6. 2019Benchmarking time series classification -- Functional data vs machine learning approachescited by 5
  7. 2015On the use of reproducing kernel Hilbert spaces in functional classificationcited by 4
  8. 2016Directional Outlyingness for Multivariate Functional Datacited by 4
  9. 2013Variable selection in functional data classification: a maxima-hunting proposalcited by 3
  10. 2018Feature selection in functional data classification with recursive maxima huntingcited by 2
  11. 2021FDApy: a Python package for functional datacited by 2
  12. 2021Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis Systemscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 5; 2026: 1.

12 papers.

  1. 2024Nonlinear functional regression by functional deep neural network with kernel embeddingcited by 7
  2. 2025Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generationcited by 7
  3. 2024Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processescited by 3
  4. 20243D-CSAD: Untrained 3D Anomaly Detection for Complex Manufacturing Surfacescited by 2
  5. 2023Functional Diffusion Mapscited by 1
  6. 2024Functional relevance based on the continuous Shapley valuecited by 1
  7. 2025Empirical risk minimization algorithm for multiclass classification of S.D.E. pathscited by 1
  8. 2025Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speedcited by 1
  9. 2024StiefelGen: A Simple, Model Agnostic Approach for Time Series Data Augmentation over Riemannian Manifoldscited by 0
  10. 2025Persistence Spheres: Bi-continuous Representations of Persistence Diagramscited by 0
  11. 2025Near-optimal Delta-convex Estimation of Lipschitz Functionscited by 0
  12. 2026Gaussian mixture models in Hilbert spaces via kernel methodscited by 0