# Introduction This lab demonstrates how to plot the decision surfaces of forests of randomized trees on the iris dataset using Python's scikit-learn library. The iris dataset is a commonly used dataset for classification tasks. In this lab, we will compare the decision surfaces learned by a decision tree classifier, a random forest classifier, an extra-trees classifier, and an AdaBoost classifier. ## 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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