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?
To minimize the distance between points in the same cluster
To maximize the distance between different clusters
To create a hierarchical structure of clusters
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.
