ECE 595ML Lecture 1.2: Linear Regression - Geometry

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 1.2: Linear Regression - Geometry," https://nanohub.org/resources/32207.

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WTHR 200, Purdue University, West Lafayette, IN

Tags

  1. algorithms
  2. linear regression
  3. machine learning
ECE 595ML Lecture 1.2: Linear Regression - Geometry
  • Lecture 1.2: Geometry 1. Lecture 1.2: Geometry 0
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  • Outline 2. Outline 13.847180513847182
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  • Linear Span 3. Linear Span 32.298965632298966
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  • Geometry of Linear Regression 4. Geometry of Linear Regression 153.85385385385385
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  • Orthogonality Principle 5. Orthogonality Principle 403.03636970303637
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  • Normal Equation 6. Normal Equation 541.54154154154151
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  • Over-determined and Under-determined Systems 7. Over-determined and Under-dete… 678.611945278612
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  • Minimum-Norm Solution 8. Minimum-Norm Solution 1057.3907240573908
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  • What if Rank-Deficient? 9. What if Rank-Deficient? 1294.6613279946614
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  • Reading List 10. Reading List 1601.5015015015015
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  • Appendix 11. Appendix 1636.6366366366367
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  • Solving the Minimum Norm problem 12. Solving the Minimum Norm probl… 1640.0734067400736
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