Example of LOF and IF benchmarks

[MaiRajborirug]

Background
The benchmarks of anomaly algorithms are important to determine the best algorithm given a dataset. The discussion in my Sklearn's PR#16378 shifted the focus from creating a quantitative benchmarks for anomaly algorithms to creating ROC examples of Local Outlier Factor (LOF) and Isolation Forest (IF). The suggestion is in the last comment of Sklearn's PR#9798

Challenges

• LOF didn't originally create for outlier detection context (training set = testing set). Thus, it doesn't have a decision_function to compute ROC curve

Plans

• Apply an algorithm in sklearn PR#9798 to create ROC in LOF
• Create ROC curves from algorithm LOF and IF, using datasets from sklearn.dataset
• After peer review and TA review, PR into "scikit-learn/scikit-learn/benchmarks"