mplot_conf: Confussion Matrix Plot

In lares: Analytics & Machine Learning Sidekick

Confussion Matrix Plot

Description

This function plots a confussion matrix.

Usage

mplot_conf(
  tag,
  score,
  thresh = 0.5,
  abc = TRUE,
  squared = FALSE,
  diagonal = TRUE,
  top = 20,
  subtitle = NA,
  model_name = NULL,
  save = FALSE,
  subdir = NA,
  file_name = "viz_conf_mat.png"
)

Arguments

tag	Vector. Real known label.
score	Vector. Predicted value or model's result.
thresh	Integer. Threshold for selecting binary or regression models: this number is the threshold of unique values we should have in 'tag' (more than: regression; less than: classification)
abc	Boolean. Arrange columns and rows alphabetically?
squared	Boolean. Force plot to be squared?
diagonal	Boolean. FALSE to convert diagonal numbers to zeroes. Ideal to detect must confusing categories.
top	Integer. Plot only the most n frequent variables. Set to NA to plot all.
subtitle	Character. Subtitle to show in plot
model_name	Character. Model's name
save	Boolean. Save output plot into working directory
subdir	Character. Sub directory on which you wish to save the plot
file_name	Character. File name as you wish to save the plot

Details

You may use conf_mat() to get calculate values.

Value

Plot with confusion matrix results.

See Also

Other ML Visualization: mplot_cuts(), mplot_cuts_error(), mplot_density(), mplot_full(), mplot_gain(), mplot_importance(), mplot_lineal(), mplot_metrics(), mplot_response(), mplot_roc(), mplot_splits(), mplot_topcats()

Examples

Sys.unsetenv("LARES_FONT") # Temporal
data(dfr) # Results for AutoML Predictions
lapply(dfr, head)

# Plot for Binomial Model
mplot_conf(dfr$class2$tag, dfr$class2$scores,
  model_name = "Titanic Survived Model"
)

# Plot for Multi-Categorical Model
mplot_conf(dfr$class3$tag, dfr$class3$score,
  model_name = "Titanic Class Model"
)

lares documentation built on Sept. 13, 2024, 1:08 a.m.