Problem 1: - Currently, the tree structure only exists in the C++ backend and is mostly inaccessible to the user in python. Proposal 1: - Create a new python/cython code that generates USPORF forest/tree structures ****************** Problem 2: - There is no outlier/anomaly detection in USPORF yet Proposal 2 - Create an outlier detection algorithms example which contain: 1. Isolation Forest (IF) from scikit-learn 2. USPORF using affinity sum row of affinity matrix to determine the outliers 3. USPORF uses **pathlength function** from [Isolation Forest paper](https://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/icdm08b.pdf?q=isolation-forest)