How can I use a custom feature selection function in scikit-learn's `pipeline`

Question

Let\'s say that I want to compare different dimensionality reduction approaches for a particular (supervised) dataset that consists of n>2 features via cross-validation and by u

Answer 1

Adding on Sebastian Raschka's and eickenberg's answers, the requirements a transformer object should hold are specified in scikit-learn's documentation.

There are several more requirements than just having fit and transform, if you want the estimator to usable in parameter estimation, such as implementing set_params.