sa_fri1:
Synthetic regression and classification datasets for measuring input importance of supervised learning models
Description
5 Synthetic regression (sa_fri1, sa_ssin, sa_psin, sa_int2, sa_tree) and 4 classification (sa_ssin_2, sa_ssin_n2p, sa_int2_3c, sa_int2_8p) datasets for measuring input importance of supervised learning models
Usage
data(sa_fri1)
Arguments
Format
A data frame with 1000 observations on the following variables.
xn
input (numeric or factor, depends on the dataset)
y
output target (numeric or factor, depends on the dataset)
Source
See references
Details
Check reference or source for full details
References
To cite the Importance function, sensitivity analysis methods or synthetic datasets, please use:
P. Cortez and M.J. Embrechts.
Using Sensitivity Analysis and Visualization Techniques to Open Black Box Data Mining Models.
In Information Sciences, Elsevier, 225:1-17, March 2013.
http://dx.doi.org/10.1016/j.ins.2012.10.039