ECE 595ML Lecture 2.1: Regularized Linear Regression

By Stanley H. Chan

Electrical and Computer Engineering, Purdue University, West Lafayette, IN

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Researchers should cite this work as follows:

  • Stanley H. Chan (2020), "ECE 595ML Lecture 2.1: Regularized Linear Regression," https://nanohub.org/resources/32208.

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WTHR 200, Purdue University, West Lafayette, IN

Tags

  1. algorithms
  2. linear regression
  3. machine learning
ECE 595ML Lecture 2.1: Regularized Linear Regression
  • Lecture 2.1: Regularization - Ridge Regression 1. Lecture 2.1: Regularization - … 0
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  • Outline 2. Outline 50.350350350350354
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  • Outline 3. Outline 141.74174174174175
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  • Ridge Regression 4. Ridge Regression 190.49049049049049
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  • Change in Eigen-values 5. Change in Eigen-values 338.304971638305
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  • Regularization Parameter λ 6. Regularization Parameter λ 511.277944611278
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  • Comparing Vanilla and Ridge 7. Comparing Vanilla and Ridge 700.266933600267
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  • Comparing Vanilla and Ridge 8. Comparing Vanilla and Ridge 879.94661327994663
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  • Geometric Interpretation 9. Geometric Interpretation 996.32966299632972
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  • Choosing λ 10. Choosing λ 1282.3156489823157
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