Educational Outlier Package with Common Outlier Detection Algorithms
DBSCAN_method
euclidean_distance
knn
z_score_method
Box And Whiskers
lof
mahalanobis_distance
mahalanobis_method
manhattan_dist
mean_outliersLearn
quantile_outliersLearn
sd_outliersLearn
transform_to_vector
Provides implementations of some of the most important outlier detection algorithms. Includes a tutorial mode option that shows a description of each algorithm and provides a step-by-step execution explanation of how it identifies outliers from the given data with the specified input parameters. References include the works of Azzedine Boukerche, Lining Zheng, and Omar Alfandi (2020) <doi:10.1145/3381028>, Abir Smiti (2020) <doi:10.1016/j.cosrev.2020.100306>, and Xiaogang Su, Chih-Ling Tsai (2011) <doi:10.1002/widm.19>.