#23: Scikit-learn 20: Preprocessing 20: Marking imputed values, MissingIndicator()
The video discusses the code for marking imputed values in Scikit-learn in Python.
Timeline
(Python 3.8)
00:00 - Outline of video
00:24 - Why mark imputed values?
03:14 - Open Jupyter notebook
03:33 - Data
04:18 - MissingIndicator: features='missing-only'
05:33 - MissingIndicator: features='all'
06:50 - Create array with missing values: x_train, y_train
09:14 - FeatureUnion: create transformer
10:22 - transformer.fit_transform()
11:51 - make_pipleline()
14:45 - Ending notes