K Means Clustering using L1 Distance Euclidean Distance Machine Learning by Dr. Mahesh Huddar

This video discusses, how to create clusters using the K-Means clustering algorithm with the L1-Distance measure.

Consider the 5 data points shown below:
P1: (1, 2, 3)
P2: (0, 1, 2)
P3: (3, 0, 5)
P4: (4, 1, 3)
P5: (5, 0, 1)
Apply the Kmeans clustering algorithm, to group those data points into 2 clusters, using the L1 distance measure.
Consider the initial centroids are C1: (1, 0, 0) and C2: (0, 1, 1).

Kmeans Solved Example: [ Ссылка ]

KMeans Algorithm: [ Ссылка ]

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