# Introduction The Local Outlier Factor (LOF) algorithm is an unsupervised machine learning method that is used to detect anomalies in data. It computes the local density deviation of a given data point with respect to its neighbors and considers as outliers the samples that have a substantially lower density than their neighbors. In this lab, we will use LOF to detect outliers in a dataset. ## 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.
Click the virtual machine below to start practicing