Machine Learning Techniques 筆記：2-2 Dual Support Vector Machine
找出最佳的線，margin最大，通過QP求解 非線性特徵轉換，只需要將原來的x轉換爲z即可。z空間的線性分類，對應到原來的x空間，可能就是一個非線性的分類動作 透過SVM，large margin，來控制模型的複雜度。透過特徵轉換得到彎曲的邊界，做好Ein 如果d quota的維度很大時，比如無窮大，則可能無法做好。怎麼辦？ 目標：只跟資料數量有關，與特徵的維度無關 原來的問題：有條件的最佳化問題
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相關文章
- 1. Machine Learning Techniques -2-Dual Support Vector Machine
- 2. Machine Learning Techniques 筆記：2-6 Support Vector Regression
- 3. Machine Learning Techniques 筆記：2-4 Soft-Margin Support Vector Machine
- 4. Machine Learning Techniques 筆記：2-3 Kernel Support Vector Machine
- 5. Machine Learning Techniques 筆記：2-1 Linear Support Vector Machine
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