# Introduction This lab demonstrates how to use Scikit-Learn to perform outlier detection on classical anomaly detection datasets using the local outlier factor (LOF) and isolation forest (IForest) algorithms. The performance of the algorithms is assessed in an outlier detection context, and ROC curves are used to plot the results. ## 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.
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