Python Outlier Detection Thresholding (PyThresh):Python离群点检测阈值决策库
Python Outlier Detection Thresholding (PyThresh):Python离群点检测阈值决策库 Python Outlier Detection Thresholding (PyThresh) - Outlier Detection Thresholding' by KulikDM
GitHub - KulikDM/pythresh: Outlier Detection Thresholding
PyThresh is a comprehensive and scalable Python toolkit for thresholding outlier detection scores in univariate/multivariate data. It has been writen to work in tandem with PyOD and has similar syntax and data structures. However, it is not limited to this single library. PyThresh is meant to threshold scores generated by an outlier detection. It thresholds scores without the need to set a contamination level or have the user guess the amount of outliers that may exist in the dataset beforehand. These non-parametric methods were written to reduce the user's input/guess work and rather rely on statistics instead to threshold outlier scores. For thresholding to be applied correctly, the outlier detection scores must follow this rule: the higher the score, the higher the probability that it is an outlier in the dataset. All threshold functions return a binary array where inliers and outliers are represented by a 0 and 1 respectively.
PyThresh includes more than 30 thresholding algorithms. These algorithms range from using simple statistical analysis like the Z-score to more complex mathematical methods that involve graph theory and topology.