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Found 4 papers, 3 papers with code
Interpretable transformed ANOVA approximation on the example of the prevention of forest fires
We demonstrate the applicability of this procedure on the well-known forest fires data set from the UCI machine learning repository.
Interpretable Approximation of High-Dimensional Data
The advantage of this method is the interpretability of the approximation, i. e., the ability to rank the importance of the attribute interactions or the variable couplings.
Grouped Transformations and Regularization in High-Dimensional Explainable ANOVA Approximation
From there we propose a fast matrix-vector multiplication, the grouped Fourier transform, for high-dimensional grouped index sets.
Numerical Analysis Numerical Analysis 65T, 42B05
Learning multivariate functions with low-dimensional structures using polynomial bases
In this paper we propose a method for the approximation of high-dimensional functions over finite intervals with respect to complete orthonormal systems of polynomials.
Numerical Analysis Numerical Analysis
