hierarchical_clusterring_analysis
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| hierarchical_clusterring_analysis [2024/11/21 14:13] – hkimscil | hierarchical_clusterring_analysis [2024/11/21 14:16] (current) – hkimscil | ||
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| - | Euclidian distance Distance | + | SA https:// |
| - | Manhattan distance (City-block) Distance | + | |
| - | Correlation Distance | + | |
| - | Eisen Cosine Correlation Distance | + | |
| - | Kendal Distance | + | |
| - | \begin{eqnarray*} | + | Cluster distance |
| + | * Single | ||
| + | * Complete | ||
| + | * Average | ||
| + | * Centroid | ||
| + | |||
| + | Method to get distance | ||
| + | * Euclidian distance Distance | ||
| + | * Manhattan distance (City-block) Distance | ||
| + | * Correlation Distance | ||
| + | * Eisen Cosine Correlation Distance | ||
| + | * Kendal Distance | ||
| + | |||
| + | |||
| + | \begin{eqnarray*} | ||
| d_{euc} (x, y) & = & \sqrt{ \sum_{i=1}^{n}(x_{i} - y_{i})^2 } \\ | d_{euc} (x, y) & = & \sqrt{ \sum_{i=1}^{n}(x_{i} - y_{i})^2 } \\ | ||
| d_{man} (x, y) & = & \sum_{i=1}^{n} | (x_{i} - y_{i}) | \\ | d_{man} (x, y) & = & \sum_{i=1}^{n} | (x_{i} - y_{i}) | \\ | ||
hierarchical_clusterring_analysis.1732166017.txt.gz · Last modified: by hkimscil