Given a set of data points as input Randomly assign each point to one of the k clusters
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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 – Assign each point to the cluster with the closest model k-means Clustering Algorithm
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k -means Clustering Algorithm. 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 Example. - PowerPoint PPT Presentation
Transcript of Given a set of data points as input Randomly assign each point to one of the k clusters
• 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
k-means Clustering Example
Randomly assign each point to one of the clusters
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Assign each point to closest cluster center
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Assign each point to closest cluster center
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Calculate center of each cluster
k-means Clustering Example
Convergence
k-means Clustering Example
Does k-means always work?
Does k-means always work?
Does k-means always work?
