| steprfAVIPredictors {steprf} | R Documentation |
Extract names of the selected predictive variables by steprf
Description
This function is to extract names of the selected predictive variables by steprfAVI.
Usage
steprfAVIPredictors(steprf1, trainx)
Arguments
steprf1 |
a list of output of 'steprf' function. |
trainx |
a dataframe or matrix contains columns of predictor variables. |
Value
A list with the following components: 1) variables.most.accurate: a list of predictive variables contained in the most accurate RF model, 2) PABV: a list of predictive variables with positive contributions to the predictive accuracy of RF models, that is, predictive accuracy boosting variable (PABV), 3) PARV: a list of predictive variables with negative contributions to the predictive accuracy of RF models, that is, predictive accuracy reducing variable, and 4) max.predictive.accuracy: the predictive accuracy of the most accurate RF model.
Author(s)
Jin Li
References
Li, J. (2022). Spatial Predictive Modeling with R. Boca Raton, Chapman and Hall/CRC.
Li, J. (2019). "A critical review of spatial predictive modeling process in environmental sciences with reproducible examples in R." Applied Sciences 9: 2048.
Li, J., Siwabessy, J., Huang, Z., and Nichol, S. (2019). "Developing an optimal spatial predictive model for seabed sand content using machine learning, geostatistics and their hybrid methods." Geosciences 9 (4):180.
Examples
library(spm)
data(petrel)
set.seed(1234)
steprf1 <- steprfAVI(trainx = petrel[, c(1,2, 6:9)], trainy = petrel[, 5],
nsim = 10, min.n.var = 2)
steprfAVIPredictors(steprf1, trainx = petrel[, c(1,2, 6:9)])