draw_confusion: Plot confusion matrix

In egenn/rtemis: Machine Learning and Visualization

Plot confusion matrix

Description

Plot confusion matrix

Usage

draw_confusion(
  x,
  xlab = "Predicted",
  ylab = "Reference",
  true_col = "#72CDF4",
  false_col = "#FEB2E0",
  font_size = 18,
  main = NULL,
  main_y = 1,
  main_yanchor = "bottom",
  theme = choose_theme(),
  margin = list(l = 20, r = 5, b = 5, t = 20),
  filename = NULL,
  file_width = 500,
  file_height = 500,
  file_scale = 1
)

Arguments

x	ClassificationMetrics object produced by classification_metrics or confusion matrix where rows are the reference and columns are the estimated classes. For binary classification, the first row and column are the positive class.
xlab	Character: x-axis label. Default is "Predicted".
ylab	Character: y-axis label. Default is "Reference".
true_col	Color for true positives & true negatives.
false_col	Color for false positives & false negatives.
font_size	Integer: font size.
main	Character: plot title.
main_y	Numeric: y position of the title.
main_yanchor	Character: y anchor of the title.
theme	Theme object.
margin	List: Plot margins.
filename	Character: file name to save the plot. Default is NULL.
file_width	Numeric: width of the file. Default is 500.
file_height	Numeric: height of the file. Default is 500.
file_scale	Numeric: scale of the file. Default is 1.

Value

plotly object.

Author(s)

EDG

Examples

## Not run: 
# Assume positive class is "b"
true_labels <- factor(c("a", "a", "a", "b", "b", "b", "b", "b", "b", "b"))
predicted_labels <- factor(c("a", "b", "a", "b", "b", "a", "b", "b", "b", "a"))
predicted_prob <- c(0.3, 0.55, 0.45, 0.75, 0.57, 0.3, 0.8, 0.63, 0.62, 0.39)
metrics <- classification_metrics(true_labels, predicted_labels, predicted_prob)
draw_confusion(metrics)

## End(Not run)

egenn/rtemis documentation built on June 14, 2025, 11:54 p.m.