Evaluating Accuracy from the ROC Curve
Explore how to evaluate the accuracy of Bayesian network models through ROC curve and area under the curve analysis. Learn to interpret true positive and false positive rates, adjust model parameters, and assess classification performance using Python.
We'll cover the following...
We'll cover the following...
In this lesson, we will examine the application of ROC curves to assess the accuracy of the complex BN model we created on the last mini-project. ROC curves offer a valuable way to compare the impact of individual features on prediction accuracy, shedding light on our model's performance.
Remember that the ROC curve, a widely used graphical representation in Bayesian network analysis, plots the true positive rate (or recall) against the false positive rate at different classification ...