Fitting sparse multidimensional data with low-dimensional terms
收藏Mendeley Data2023-02-23 更新2024-06-26 收录
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Abstract
An algorithm that fits a continuous function to sparse multidimensional data is presented. The algorithm uses a representation in terms of lower-dimensional component functions of coordinates defined in an automated way and also permits dimensionality reduction. Neural networks are used to construct the component functions.
Title of program: RS_HDMR_NN
Catalogue Id: AEEI_v1_0
Nature of problem
Fitting a smooth, easily integratable and differentiatable, function to a very sparse (~2-3 points per dimension) multidimensional (D >= 6) large (~10 4 -10 5 data) dataset.
Versions of this program held in the CPC repository in Mendeley Data
AEEI_v1_0; RS_HDMR_NN; 10.1016/j.cpc.2009.05.022
This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
创建时间：
2020-01-06
