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Given a set of data points as input Randomly assign each point to one of the k clusters Repeat until convergence – Calculate model of each of the k clusters.

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Presentation on theme: "Given a set of data points as input Randomly assign each point to one of the k clusters Repeat until convergence – Calculate model of each of the k clusters."— Presentation transcript:

1 Given a set of data points as input Randomly assign each point to one of the k clusters Repeat until convergence – Calculate model of each of the k clusters – Assign each point to the cluster with the closest model k-means Clustering Algorithm

2 k-means Clustering Example

3 Randomly assign each point to one of the clusters k-means Clustering Example

4 Calculate center of each cluster k-means Clustering Example

5 Calculate center of each cluster k-means Clustering Example

6 Calculate center of each cluster k-means Clustering Example

7 Assign each point to closest cluster center k-means Clustering Example

8 Calculate center of each cluster k-means Clustering Example

9 Calculate center of each cluster k-means Clustering Example

10 Calculate center of each cluster k-means Clustering Example

11 Assign each point to closest cluster center k-means Clustering Example

12 Calculate center of each cluster k-means Clustering Example

13 Calculate center of each cluster k-means Clustering Example

14 Calculate center of each cluster k-means Clustering Example

15 Convergence k-means Clustering Example

16 Does k-means always work?

17

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