Question

Which of the following statements are correct?

1. K-means clustering is a method of vector quantization

2. K-means clustering aims to partition n observations into k clusters

3. K-nearest neighbor is same as k-means

4. K-means clustering is a type of supervised learning​

Answer 1

2. K-means clustering aims to partition n observations into k clusters

Answer 2

Which of the following statements are correct?

1. K-means clustering is a method of vector quantization

2. K-means clustering aims to partition n observations into k clusters

3. K-nearest neighbor is same as k-means

4. K-means clustering is a type of supervised learning​

The correct answer is :

1. K-means clustering is a method of vector quantization

Explanation :

k-means clustering is basically a method of vetor quantisztion than signal processing. The main purpose of this method is to divide the 'n' observations 'k' cluster.

In this method each observation is related to the cluster with the nearest mean. This observation serves as a cluster. This cluster serves as a prototype. For this reason the data space is divided into Voronai cells.

k-means clustering minimizes individual variance within a cluster. k-means clustering minimizes the geometric median Euclidean distances.

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