Cooks distance unsupervised

[KulikDM]

All Submissions Basics:

• 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:

• 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?
• Have you successfully ran tests with your changes locally?
• 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:

• 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?

I originally authored the Cook's distance outlier detection method on PyOD. But upon review, I realized that the method is not consistent with the rest of this library as the method is currently a supervised one. The changes made now have updated this method to be in line with the rest of the library by making it an unsupervised method.

The most significant change is that instead of evaluating the model predictions against the response variable (y) the model now evaluates each variable in X against the rest of the variables in X and then computes the mean Cook's distance for each datapoint.

[coveralls]

Pull Request Test Coverage Report for Build 4518347268

• 35 of 36 (97.22%) changed or added relevant lines in 2 files are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage increased (+0.05%) to 93.602%

---

Changes Missing Coverage	Covered Lines	Changed/Added Lines	%
pyod/models/cd.py	27	28	96.43%

Totals
Change from base Build 4463703550:	0.05%
Covered Lines:	8705
Relevant Lines:	9300

---

💛 - Coveralls