Is it possible to mask outliers within a scikit learn pipeline?
There's no support for masking in scikit-learn; outlier detection is done ad hoc by some estimators (e.g. DBSCAN, or RANSAC, which will appear in the next release).
If you want to remove outliers yourself, just use NumPy indexing.
I have a pipeline where I transform some data and fit a curve to it. Is there a preferred/standard way for masking the outliers in the data?