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Create a discriminant analysis decision plot using ggplot.

Source: R/plot_discrim.R
plot_discrim.Rd

Discriminant analysis can be more easily understood from plots of the data variables showing how observations are classified. plot_discrim() uses the ideas behind effect plots: Visualize predicted values for two focal variables, with other variables in a model held fixed.

Usage

plot_discrim(
  model,
  vars,
  data,
  resolution = 100,
  contour = TRUE,
  contour.color = "black",
  point.size = 3,
  showgrid = c("tile", "point", "none"),
  ...,
  modes.means
)

Arguments

model

a discriminant analysis model object from MASS::lda() or MASS::qda()

vars

either a character vector of length 2 of the names of variables, or a formula of form V1 ~ V2 specifying y and x axis in the plot respectively.

data

data to use for visualization. Should contain all the data needed to use the model

resolution

number of points in x, y variables to use for visualizating the predicted class boundaries and regions.

contour

logical; should the plot display the boundaries of the classes by contours?

contour.color

colour of the lines for the contour boundaries

point.size

size of the plot symbols use to show the data observations

showgrid

a character string; how to display predicted class regions: "tile" for geom_tile, "point" for geom_point, or "none" for no grid display.

...

further parameters passed to predict()

modes.means

levels to use for evaluating predictions using the variables *not specified in vars. If not specified, the function uses the means for quantitative variables, ...

Details

In setting up this plot for ggplot(), this function maps color and shape of class-specific elements of the plot to the value of the class variable in the discriminant analysis. But it simply uses the ggplot defaults...

See also

klaR::partimat()

Author

Original code by Oliver on SO https://stackoverflow.com/questions/63782598/quadratic-discriminant-analysis-qda-plot-in-r. Generalized by Michael Friendly

Examples

library(MASS)
#> 
#> Attaching package: 'MASS'
#> The following object is masked from 'package:dplyr':
#> 
#>     select
library(ggplot2)
library(dplyr)

iris.lda <- lda(Species ~ ., iris)
plot_discrim(iris.lda, Petal.Length ~ Petal.Width, data=iris, showgrid = "tile")
#> Error in plot_discrim(iris.lda, Petal.Length ~ Petal.Width, data = iris,     showgrid = "tile"): could not find function "plot_discrim"