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Q3) Use make_regression function in skearn to generate dataset with 500 samples with 15 features with random_state=10. a. Split the dataset into 70% train data and 30% test data. b. Use sklearn to implement the following: • Linear regression Lasso regression Ridge regression Rolyno mial lin ear rooroccionn

Q3) Use make_regression function in skearn to generate dataset with 500 samples with 15 features with random_state=10. a. Split the dataset into 70% train data and 30% test data. b. Use sklearn to implement the following: • Linear regression Lasso regression Ridge regression Rolyno mial lin ear rooroccionn

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Q3) Use make_regression function in skearn to generate dataset with 500 samples with 15 features with random_state=10. a. Split the dataset into 70% train data and 30% test data. b. Use sklearn to implement the following: • Linear regression • Lasso regression • Ridge regression Polynomial linear regression c. Draw bar chart or table that compares the mean squared error between the correct outputs and the predicted outputs on testing set for linear models.
Transcribed Image Text:Q3) Use make_regression function in skearn to generate dataset with 500 samples with 15 features with random_state=10. a. Split the dataset into 70% train data and 30% test data. b. Use sklearn to implement the following: • Linear regression • Lasso regression • Ridge regression Polynomial linear regression c. Draw bar chart or table that compares the mean squared error between the correct outputs and the predicted outputs on testing set for linear models.
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