Fast and Provably Good Seedings for k-means
本文主要介紹關於k-means++改進相關的兩篇文章： 1. Fast and Provably Good Seedings for k-means 2. Approximate K-menas++ in Sublinear Timeweb k-means++ 相對於 k-menas的算法改進主要在於聚類中心的初始化階段。算法 如圖所示，左邊是原始k-means 算法的初始化階段，原始算隨機選擇
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相關文章
- 1. Fast and Provably Good Seedings for k-means
- 2. Fast and Provably Good Seedings for k-Means閱讀筆記
- 3. Semantic Flow for Fast and Accurate Scene Parsing
- 4. Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
- 5. PEPSI++: Fast and Lightweight Network for Image Inpainting | 簡記
- 6. Why Good Programmers Are Lazy and Dumb
- 7. Games201_lecture5_PossionsEquation and Fast Method
- 8. Reinforcement Learning, Fast and Slow
- 9. What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?
- 10. How to Design a Good API and Why it Matters