18. 17
Iteration = 0
1. Start with random positions of centroids.
K-Means Illustrations
19. 18
Iteration = 1
1. Start with random positions of centroids.
2. Assign each data point to closest centroid
K-Means Illustrations
20. 19
Iteration = 1
1. Start with random positions of centroids.
2. Assign each data point to closest centroid
3. Move centroids to center of assigned
points (recalculating C)
K-Means Illustrations
21. 20
Iteration = 3
1. Start with random positions of centroids.
2. Assign each data point to closest centroid
3. Move centroids to center of assigned
points
4. Iterate till minimal cost
K-Means Illustrations
22. 21
Iteration = 3
1. Start with random positions of centroids.
2. Assign each data point to closest centroid
3. Move centroids to center of assigned
points
4. Iterate till minimal cost
What potentially can go wrong?
23. 22
Optimum Number of Cluster Illustrations
TSS = Total Sum of Square Error
K = Number of cluster
Optimum Number of Cluster