Week8_3Program_K-Means Clustering and PCA編程解析
Week8_3Program_K-Means Clustering and PCA編程解析 1. ex7 流程分析 1.1 plotData 按照ex7.m中的流程走一遍python 2. 編程分析 2.1 Find closest centroids 0 / 30 計算公式: ||x(i)−μj||2 | | x ( i ) − μ j | | 2 X=(300x2) K=3 centroids
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相關文章
- 1. [CS131] Lecture 10 Semantic Segmentation and Clustering
- 2. w6_2Regularized Linear Regression and BiasVariance編程解析
- 3. w4_2Multi-class Classification and Neural Networks編程解析
- 4. Week9_3Program_Anomaly Detection and Recommender Systems編程解析
- 5. Kernel Clustering: Density Biases and Solutions
- 6. BIRCH：Balanced Iterative Reducing and Clustering Using Hierarchis
- 7. PCA原理解析
- 8. [Scikit-learn] 2.3 Clustering - Spectral clustering
- 9. PCA(主成分分析)過程詳解
- 10. Machine learning 第8周編程作業 K-means and PCA