mIshigami: Dataset mIshigami
In NNbenchmark: Datasets and Functions to Benchmark Neural Network Packages
Description
References
Examples
Description
A multivariate dataset (x1, x2, x3, y) of class matrix and dim 500 x 4 to be fitted
by a neural network with 10 hidden neurons (51 parameters).
References
Ishigami, T., & Homma, T. (1990, December). An importance quantification technique in
uncertainty analysis for computer models. In Uncertainty Modeling and Analysis, 1990.
Proceedings., First International Symposium on (pp. 398-403). IEEE.
See also https://www.sfu.ca/~ssurjano/ishigami.html
Examples
1
2
NNbenchmark documentation built on June 5, 2021, 5:06 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description References Examples
Description
A multivariate dataset (x1, x2, x3, y) of class matrix and dim 500 x 4 to be fitted by a neural network with 10 hidden neurons (51 parameters).
References
Ishigami, T., & Homma, T. (1990, December). An importance quantification technique in uncertainty analysis for computer models. In Uncertainty Modeling and Analysis, 1990. Proceedings., First International Symposium on (pp. 398-403). IEEE.
See also https://www.sfu.ca/~ssurjano/ishigami.html
Examples
1 2 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.