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* K Means Clustering is used here to perform this task.
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### What is K Means Clustering ?
Kmeans algorithm is an iterative algorithm that tries to partition the dataset into Kpre-defined distinct non-overlapping subgroups (clusters) where each data point belongs to only one group.
* This algorithm basically follow 4 steps.
1. It first randomly intialize centres.
2. It computes the distance of each point from each center and associates the point to that center from which its Eucledian distance is minimum. (```Euclidean Distance between two points ((x,y),(a,b)) is given as = √(x - a)² + (y - b)²```)
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