mplot3_varimp: 'mplot3': Variable Importance
In egenn/rtemis: Machine Learning and Visualization

mplot3_varimp

R Documentation

`mplot3`: Variable Importance

Description

Draw horizontal barplots for variable importance

Usage

mplot3_varimp(
  x,
  error = NULL,
  names = NULL,
  names.pad = 0.02,
  plot.top = 1,
  labelify = TRUE,
  col = NULL,
  palette = rtPalette,
  alpha = 1,
  error.col = theme$fg,
  error.lwd = 2,
  beside = TRUE,
  border = NA,
  width = 1,
  space = 0.75,
  xlim = NULL,
  ylim = NULL,
  xlab = "Variable Importance",
  xlab.line = 1.3,
  ylab = NULL,
  ylab.line = 1.5,
  main = NULL,
  names.arg = NULL,
  axisnames = FALSE,
  sidelabels = NULL,
  mar = NULL,
  pty = "m",
  barplot.axes = FALSE,
  xaxis = TRUE,
  x.axis.padj = -1.2,
  tck = -0.015,
  theme = rtTheme,
  zerolines = FALSE,
  par.reset = TRUE,
  autolabel = letters,
  pdf.width = NULL,
  pdf.height = NULL,
  trace = 0,
  filename = NULL,
  ...
)

Arguments

`x`	Vector, numeric: Input
`error`	Vector, numeric; length = length(x): Plot error bars with given error.
`names`	Vector, string; optional: Names of variables in `x`
`plot.top`	Float or Integer: If <= 1, plot this percent highest absolute values, otherwise plot this many top values. i.e.: `plot.top = .2` will print the top 20% highest values, and `plot.top = 20` will plot the top 20 highest values
`labelify`	Logical: If TRUE convert `names(x)` using labelify. Default = TRUE
`col`	Colors: Gradient to use for barplot fill.
`alpha`	Float (0, 1): Alpha for `col`
`error.col`	Color: For error bars
`trace`	Integer: If `trace > 0` prints out the automatically set `mar` (so you can adjust if needed) `names` provided