Basis Function Expansion
Basis Function Expansion is a mathematical technique in regression analysis that extends a set of input features by transforming them into a higher-dimensional space through the application of predefined basis functions, such as polynomial terms, to capture nonlinear relationships while maintaining linearity in model parameters.
405
Publications
46.4K
Citations
1K
Authors
449
Institutions
Publications per year
2017–2026
70
Parents
405
Multivariate Adaptive Regression Splines
Jerome H. Friedman · The Annals of Statistics · 1991 · 8.1K citations · Full text
Fuzzy logic systems for engineering: a tutorial
Jerry M. Mendel · Proceedings of the IEEE · 1995 · 2.1K citations
1–5 of 405
1K
10
h-index
6
h-index
4
h-index
4
h-index
3
h-index
1–5 of 1K
449

University of Minnesota
Minneapolis, United States
9 h-index
18 publications
1.3K citations

Delft University of Technology
Delft, The Netherlands
8 h-index
13 publications
1.4K citations
Duke University
Durham, United States
7 h-index
16 publications
1.3K citations
University of California, Berkeley
Berkeley, United States
7 h-index
17 publications
3.6K citations
Iowa State University
Ames, United States
7 h-index
20 publications
2.4K citations

Lawrence Livermore National Laboratory
Livermore, United States
7 h-index
18 publications
388 citations
KU Leuven
Leuven, Belgium
6 h-index
12 publications
803 citations
University of Michigan
Ann Arbor, United States
6 h-index
12 publications
578 citations
1–8 of 449
34 publications · 14.1K citations
25
h-index
9 publications · 762 citations
9
h-index
9 publications · 523 citations
9
h-index
Repository · 7 publications · 148 citations
7
h-index
PRA · 7 publications · 353 citations
7
h-index
1–5