ECE 595ML Lecture 19.2: Support Vector Machine - SVM

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 19.2: Support Vector Machine - SVM," https://nanohub.org/resources/32749.

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WTHR 200, Purdue University, West Lafayette, IN

ECE 595ML Lecture 19.2: Support Vector Machine - SVM
  • Lecture 19.2: Support Vector Machine (SVM) 1. Lecture 19.2: Support Vector M… 0
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  • Outline 2. Outline 8.6086086086086091
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  • Unfortunately ... 3. Unfortunately ... 26.326326326326328
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  • Trick 1: Scaling 4. Trick 1: Scaling 41.07440774107441
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  • Trick 1: Scaling 5. Trick 1: Scaling 180.24691358024691
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  • Eliminate γ 6. Eliminate γ 238.83883883883885
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  • Eliminate γ 7. Eliminate γ 332.23223223223226
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  • Trick 2: Max to Min 8. Trick 2: Max to Min 502.23556890223557
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  • Hand Crafted Example 9. Hand Crafted Example 720.98765432098764
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  • Hand Crafted Example 10. Hand Crafted Example 811.34467801134474
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  • Hand Crafted Example 11. Hand Crafted Example 909.5428762095429
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  • Writing Your SVM 12. Writing Your SVM 1058.5251918585252
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  • Writing Your SVM 13. Writing Your SVM 1113.1464798131465
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  • Comparing SVM and Bayesian Oracle 14. Comparing SVM and Bayesian Ora… 1167.9012345679014
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  • MATLAB Code for 2D SVM 15. MATLAB Code for 2D SVM 1208.641975308642
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  • SVM in 2D 16. SVM in 2D 1221.7884551217885
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  • Displaying Results 17. Displaying Results 1268.868868868869
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  • Reading List 18. Reading List 1281.9486152819486
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