kerntools (version 1.2.0)

plotImp: Importance barplot

Description

`plotImp()` displays the barplot of a numeric vector, which is assumed to contain the features importance (from a prediction model) or the contribution of each original variable to a Principal Component (PCA). In the barplot, features/PCs are sorted by decreasing importance.

Usage

plotImp(
  x,
  y = NULL,
  relative = TRUE,
  absolute = TRUE,
  nfeat = NULL,
  names = NULL,
  main = NULL,
  xlim = NULL,
  color = "grey",
  leftmargin = NULL,
  ylegend = NULL,
  leg_pos = "right",
  ...
)

Value

A list containing:

* The vector of importances in decreasing order. When `nfeat` is not NULL, only the top `nfeat` are returned.

* The cumulative sum of (absolute) importances.

* A numeric vector giving the coordinates of all the drawn bars' midpoints.

Arguments

x

Numeric vector containing the importances.

y

(optional) Numeric vector containing a different, independent variable to be contrasted with the feature importances. Should have the same length and order than `x`.

relative

If TRUE, the barplot will display relative importances. (Defaults: TRUE).

absolute

If FALSE, the bars may be positive or negative, which will affect the order of the features Otherwise, the absolute value of `x` will be taken (Defaults: TRUE).

nfeat

(optional) The number of top (most important) features displayed in the plot.

names

(optional) The names of the features, in the same order than `x`.

main

(optional) Plot title.

xlim

(optional) A numeric vector. If absent, the minimum and maximum value of `x` will be used to establish the axis' range.

color

Color(s) chosen for the bars. A single value or a vector. (Defaults: "grey").

leftmargin

(optional) Left margin space for the plot.

ylegend

(optional) It allows to add a text explaining what is `y` (only if `y` is not NULL).

leg_pos

If `ylegend` is TRUE, the position of the legend. (Defaults: "right").

...

(optional) Additional arguments (such as `axes`, `asp`,...) and graphical parameters (such as `par`). See `?graphics::barplot()`.

Examples

importances <- rnorm(30)
names_imp <- paste0("Feat",1:length(importances))

plot1 <- plotImp(x=importances,names=names_imp,main="Barplot")
plot2 <- plotImp(x=importances,names=names_imp,relative=FALSE,
main="Barplot",nfeat=10)
plot3 <- plotImp(x=importances,names=names_imp,absolute=FALSE,
main="Barplot",color="coral2")