…cated samples

Previously, when the dataset had values repeat more times than the algorithm's number of neighbors, it miscalculates the outliers.
Because the distance between the duplicated samples is 0, the local reachability density is equal to 1e10. This leads to values that are close to the duplicated values having a really low negative outlier factor (under -1e7), labeling them as outliers.
This fix checks if the minimum negative outlier factor is under -1e7 and, if so, raises the number of neighbors to the number of occurrences of the most frequent value + 1, also raising a warning.
Notes: Added a handle_duplicates variable, which allows developers to manually handle the duplicate values, if desired. Also added a memory_limit variable to avoid creating memory errors for really large datasets, which can also be changed manually by developers.

Removed automatic change to neighbors number and changed the warning
Also changed the associated test, to catch the warning.

Changed comment according to review

Co-authored-by: Tim Head <betatim@gmail.com>