Based on the Python regression example code that I explained in the video, apply the polynomial feature and fit the diabetes data set. Plot your new model and compare it with the linear model that I explained by finding the mean squared errors.

Based on the Python regression example code that I explained in the video, apply the polynomial feature and fit the diabetes data set. Plot your new model and compare it with the linear model that I explained by finding the mean squared errors.

Problem 2:

One of the data sets that can be found in SKlearn in python is boston. You can load it using load_boston. Follow the steps we followed for the diabetes data set to fit this dataset using linear regression.

The post Based on the Python regression example code that I explained in the video, apply the polynomial feature and fit the diabetes data set. Plot your new model and compare it with the linear model that I explained by finding the mean squared errors. appeared first on Versed Writers.

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