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What is the primary objective of the K-means clustering algorithm?

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Question: What is the primary objective of the K-means clustering algorithm?

Options:

  1. To minimize the distance between points in the same cluster
  2. To maximize the distance between different clusters
  3. To create a hierarchical structure of clusters
  4. To classify data into predefined categories

Correct Answer: To minimize the distance between points in the same cluster

Solution: 

K-means aims to minimize the distance between points within the same cluster by assigning points to the nearest centroid.

What is the primary objective of the K-means clustering algorithm?

Practice Questions

Q1
What is the primary objective of the K-means clustering algorithm?
  1. To minimize the distance between points in the same cluster
  2. To maximize the distance between different clusters
  3. To create a hierarchical structure of clusters
  4. To classify data into predefined categories

Questions & Step-by-Step Solutions

What is the primary objective of the K-means clustering algorithm?
Correct Answer: K-means clustering algorithm ka primary objective hai ki woh points ko unke nearest centroid ke saath assign karein, taaki same cluster ke andar points ke beech distance minimize ho sake.
  • Step 1: Understand that K-means is a method used to group similar data points together.
  • Step 2: Know that each group is called a 'cluster'.
  • Step 3: Realize that K-means uses 'centroids', which are the center points of each cluster.
  • Step 4: Learn that the goal of K-means is to make sure that data points in the same cluster are as close to each other as possible.
  • Step 5: Understand that K-means does this by assigning each data point to the nearest centroid.
  • Step 6: Remember that the overall aim is to minimize the distance between points in the same cluster.
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