fsrftest
Univariate feature ranking for regression using F-tests
Syntax
Description
ranks features (predictors) using F-tests. The table idx
= fsrftest(Tbl
,ResponseVarName
)Tbl
contains predictor variables and a response variable, and ResponseVarName
is the name of the response variable in Tbl
. The function returns idx
, which contains the indices of predictors ordered by predictor importance, meaning idx(1)
is the index of the most important predictor. You can use idx
to select important predictors for regression problems.
specifies additional options using one or more name-value pair arguments in addition to any of the input argument combinations in the previous syntaxes. For example, you can specify categorical predictors and observation weights.idx
= fsrftest(___,Name,Value
)
Examples
Input Arguments
Name-Value Arguments
Output Arguments
Algorithms
References
[1] Rasmussen, C. E., R. M. Neal, G. E. Hinton, D. van Camp, M. Revow, Z. Ghahramani, R. Kustra, and R. Tibshirani. The DELVE Manual, 1996.
[2] University of Toronto, Computer Science Department. Delve Datasets.
[3] Nash, W.J., T. L. Sellers, S. R. Talbot, A. J. Cawthorn, and W. B. Ford. "The Population Biology of Abalone (Haliotis species) in Tasmania. I. Blacklip Abalone (H. rubra) from the North Coast and Islands of Bass Strait." Sea Fisheries Division, Technical Report No. 48, 1994.
[4] Waugh, S. "Extending and Benchmarking Cascade-Correlation: Extensions to the Cascade-Correlation Architecture and Benchmarking of Feed-forward Supervised Artificial Neural Networks." University of Tasmania Department of Computer Science thesis, 1995.
[5] Lichman, M. UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science, 2013. http://archive.ics.uci.edu/ml.
Version History
Introduced in R2020a