#52: Scikit-learn 49:Supervised Learning 27: Robustness regression

Описание: The video discusses the code for Robustness Regression algorithms RANSACRegressor, TheilSenRegressor, and HuberRegressor using Scikit-learn in Python.

Timeline
(Python 3.8)

00:00 - Outline of video
00:25 - Open Jupyter notebook
00:43 - Data: using .make_regression()
01:45 - Data: create outilers
03:47 - Data: plot inliers and outliers
05:02 - LinearRegressor()
08:19 - RANSACRegressor()
09:40 - TheilSenRegressor()
10:07 - HuberRegressor()
12:24 - Data: using np.sin()
13:11 - Data: create outliers
16:19 - Create list of estimators: LinearRegression(), RANSACRegressor(), TheilSenRegressor(), HuberRegressor()
17:44 - For loop to iterate over estimators and data with different outliers for plotting
23:16 - Inlier and outlier plots
25:04 - Ending notes