scikit-fda: A Python']Python Package for Functional Data Analysis

被引:6
作者
Ramos-Carreno, Carlos [1 ]
Carbajo-Berrocal, Miguel [2 ]
Torrecilla, Jose Luis [3 ]
Marcos, Pablo [2 ]
Suarez, Alberto [1 ]
机构
[1] Univ Autonoma Madrid, Escuela Politecn Super, Dept Comp Sci, Madrid 28049, Spain
[2] Univ Autonoma Madrid, Madrid, Spain
[3] Univ Autonoma Madrid, Fac Ciencias, Dept Math, Madrid 28049, Spain
来源
JOURNAL OF STATISTICAL SOFTWARE | 2024年 / 109卷 / 02期
关键词
functional data analysis; computational statistics; interactive data visualization; !text type='Python']Python[!/text; scikit-learn; FEATURE-SELECTION; CLASSIFICATION; REDUCTION; REGRESSION; MODELS; DEPTH;
D O I
10.18637/jss.v109.i02
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:1 / 37
页数:37
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