Question

The most commonly used distance metric to calculate distance between centroid of each cluster and data points in k-means algorithm is

Answer 1

Explanation:

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Answer 2

Euclidean distance measure is used to distance metric to calculate distance between centroid of each cluster and data points in K-means algorithm.

Definition of Euclidean distance measure;

Euclidean distance measure is sued to find the distance between the center points and data points.

Uses of Euclidean distance measure;

• Euclidean distance measure is a part of machine learning. It is used to measure the distance between the algorithm that means the center point and data points.
• It is responsible for giving the direction from each cell to the closest source.

• To identify the cell and the distance of the allocated source.
• The distance measured is 3 dimensional space measures connecting two points.

Therefore, K-means algorithm where the distance is measured is called the euclidean distance measure responsible for allocating the distance between the two pints of cell.