All Submissions Basics:
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Have you followed the guidelines in our Contributing document? -
Have you checked to ensure there aren't other open Pull Requests for the same update/change? -
Have you checked all Issues to tie the PR to a specific one?
All Submissions Cores:
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Have you added an explanation of what your changes do and why you'd like us to include them? -
Have you written new tests for your core changes, as applicable? -
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Does your submission pass tests, including CircleCI, Travis CI, and AppVeyor? -
Does your submission have appropriate code coverage? The cutoff threshold is 95% by Coversall.
New Model Submissions:
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Have you created a .py in ~/pyod/models/? -
Have you created a _example.py in ~/examples/? -
Have you created a test_.py in ~/pyod/test/? -
Have you lint your code locally prior to submission?
Median Absolute Deviation (MAD) for detecting outliers in Univariate Data. It is one of the most reliable and robust outliers algorithms for one-dimensional data where it doesn't require the data to have Gaussian-like Distribution.