Semi-Supervised Classifiers on the Iris Dataset

# Introduction

In this lab, we will explore semi-supervised classifiers on the Iris dataset. We will compare the decision boundaries generated by Label Spreading, Self-training, and Support Vector Machine (SVM) on the Iris dataset. We will use scikit-learn, a popular Python machine learning library, to implement the classifiers and visualize the decision boundaries.

## 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.