Thresholding Outlier Detection Scores with PyThresh

Methods to replace the necessity of a contamination level in outlier detection

Real life is often chaotic and unpredictable. It seems to like throwing the metaphorical “spanner in the works”, making data usually appear baffling and random. Most data that is recorded or extracted generally requires some form of cleaning before applying further methods like modeling. However, it is often difficult or near impossible to visually distinguish what data is true, noise, or an …

data cleaning detection outlier-detection thresholding