plot_confusion_matrix: Plotting Confusion Matrix

In MLwrap: Machine Learning Modelling for Everyone

Plotting Confusion Matrix

Description

The plot_confusion_matrix() function generates confusion matrices for both training and test data in classification problems. This visualization allows evaluation of classification accuracy by category and identification of confusion patterns between classes, providing insights into which classes are most frequently misclassified.

Usage

plot_confusion_matrix(analysis_object)

Arguments

analysis_object

Fitted analysis_object with 'fine_tuning()'.

Value

analysis_object

Examples

# Note: For obtaining confusion matrix plot the user needs to
# complete till fine_tuning( ) function of the MLwrap pipeline and
# only with categorical outcome.



wrap_object <- preprocessing(df = sim_data,
                             formula = psych_well_bin ~ depression + emot_intel + resilience,
                             task = "classification")
wrap_object <- build_model(wrap_object, "Random Forest")
wrap_object <- fine_tuning(wrap_object, "Bayesian Optimization")

# And then, you can obtain the confusion matrix plot.

plot_confusion_matrix(wrap_object)

MLwrap documentation built on Aug. 8, 2025, 6:43 p.m.