avi {spm}

Averaged variable importance based on random forest

Description

This function is to derive an averaged variable importance based on random forest

Usage

avi(
  trainx,
  trainy,
  mtry = if (!is.null(trainy) && !is.factor(trainy)) max(floor(ncol(trainx)/3), 1) else
    floor(sqrt(ncol(trainx))),
  ntree = 500,
  importance = TRUE,
  maxk = c(4),
  nsim = 100,
  corr.threshold = 0.5,
  ...
)

Arguments

trainx

a dataframe or matrix contains columns of predictor variables.

trainy

a vector of response, must have length equal to the number of rows in trainx.

mtry

a function of number of remaining predictor variables to use as the mtry parameter in the randomForest call.

ntree

number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times. By default, 500 is used.

importance

imprtance of predictive variables.

maxk

maxk split value. By default, 4 is used.

nsim

iteration number. By default, 100 is used.

corr.threshold

correlation threshold and the defaults value is 0.5.

...

other arguments passed on to randomForest.

Value

A list with the following components: averaged variable importance (avi), column number of importance variable in trainx arranged from the most important to the least important (impvar), names of importance variable arranged from the most important to the least important (impvar2)

Author(s)

Jin Li

References

Smith, S.J., Ellis, N., Pitcher, C.R., 2011. Conditional variable importance in R package extendedForest.

Li, J. 2013. Predicting the spatial distribution of seabed gravel content using random forest, spatial interpolation methods and their hybrid methods. Pages 394-400 The International Congress on Modelling and Simulation (MODSIM) 2013, Adelaide.

Liaw, A. and M. Wiener (2002). Classification and Regression by randomForest. R News 2(3), 18-22.

Examples

## Not run: 
data(petrel)
set.seed(1234)
avi1 <- avi(petrel[, c(1,2, 6:9)], petrel[, 5], nsim = 10)
avi1

avi1 <- avi(petrel[, c(1), drop = FALSE], petrel[, 5], nsim = 10)
avi1

## End(Not run)