Detection Error Tradeoff Curve

# Introduction In this tutorial, we will learn about Detection Error Tradeoff (DET) curves and compare them with Receiver Operating Characteristic (ROC) curves. DET curves are a variation of ROC curves, where False Negative Rate (FNR) is plotted on the y-axis instead of the True Positive Rate (TPR). We will use scikit-learn, a popular Python library for machine learning, to generate synthetic data and compare the statistical performance of two classifiers across thresholds using ROC and DET curves. ## VM Tips After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice. Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook. If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

|60 : 00

Click the virtual machine below to start practicing