partialPlot2var: creates 3-dimensional surface plots for bivariate partial...
In Jromero1208/PBDRiRF: iterative Random Forests

Description Usage Arguments Value Author(s) See Also

Given two feature vectors and a response vector, produces surface maps of partial dependence function. Uses R package rgl

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  partialDep2var(x1, x2, y, gridlength=NULL, x1_grid=NULL, x2_grid=NULL,
x1lab='v1', x2lab='v2', ylab=NA, range.color=NULL, col.palette=c('blue',
'yellow'), plot_quantile_scale = TRUE, plot.colorbar=TRUE, ...)

`x1, x2, y`	numeric vectors containing the first, second and the response variable
`gridlength`	If either x1_grid or x2_grid is missin, a scalar indicating length of grids against which to make the plot
`x1_grid, x2_gris`	grids of points between which the surface map will be constant
`x1lab, x2lab, ylab`	Labels of x, y and z-axis respectively
`range.color`	range of values which should be colored. input in the form (min, max). If not provided, the program automatically sets it to the range of the partial dependence function calculated on grid points
`col.palette`	Color palette, typically a vector of length 2 indicating the range of colors
`plot_quantile_scale`	If TRUE, plots against quantiles of x1 and x2 instead of their raw values
`plot.colorbar`	produce a separate colorbar for the partial dependence plot?