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K-MEAN Clustering Dr. Fizar Ahmed

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K-MEAN Clustering

Dr. Fizar Ahmed

What is k-mean clustering

K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups (clusters) where each data point belongs to only one group.

The way kmeans algorithm works is as follows:

● Specify number of clusters K.● Initialize centroids by first shuffling the dataset and then randomly

selecting K data points for the centroids without replacement.● Keep iterating until there is no change to the centroids. i.e

assignment of data points to clusters isn’t changing.● Compute the sum of the squared distance between data points and

all centroids.● Assign each data point to the closest cluster (centroid).● Compute the centroids for the clusters by taking the average of the

all data points that belong to each cluster.

Page 4: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Flowchart of k-means clustering algorithm

Page 5: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Application of K-MEAN Clustering

Page 6: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 7: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 8: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 9: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 10: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 11: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 12: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 13: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 14: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 15: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 16: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 17: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 18: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 19: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 20: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 21: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 22: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Page 23: K-MEAN Clustering · What is k-mean clustering K-mean clustering is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups

Thank you

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