#6: Scikit-learn 4: Preprocessing 4: Scaling data with outliers using RobustScaler
The video discusses how to and how not-to scale data with outliers and use of RobustScaler in Scikit-learn in Python.
Timeline
(Python 3.8)
00:00 - Welcome
00:17 - Outline of video
00:42 - Suggested steps in scaling
01:10 - Why use .RobustScaler() with outliers?
03:48 - Open Jupyter notebook
04:18 - Create data with outliers
04:18 - ------- CORRECTION ------ "I meant to say 'rows' while creating the array" (and not 'columns')
04:57 - Outlier data: RobustScaler: .fit() and .transform()
06:22 - Outlier data: StandardScaler: .fit() and .transform()
07:00 - Outlier data: MaxAbsScaler: .fit() and .transform()
07:14 - Outlier data: MinMaxScaler: .fit() and .transform()
07:32 - Create data with outliers
09:00 - Outlier data: MinMaxScaler: .fit_transform()
09:53 - Outlier data: RobustScaler: .fit_transform()
10:48 - Ending notes