The K-Means algorithm terminates when:_______

a. a user-defined minimum value for the summation of squared error differences between instances and their corresponding cluster center is seen.
b. the cluster centers for the current iteration are identical to the cluster centers for the previous iteration.
c. the number of instances in each cluster for the current iteration is identical to the number of instances in each cluster of the previous iteration.
d. the number of clusters formed for the current iteration is identical to the number of clusters formed in the previous iteration.

K-mean algorithm is one of the mot widely used algorithm for partitioning into groups of k clusters. This is done by partitioning observations into clusters which are similar to each other. When using k-mean algorithm, each of the different clusters are represented by their centroid and each point are placed only in clusters in which the point is close to cluster centroid.

The K-Means algorithm terminates when the cluster centers for the current iteration are identical to the cluster centers for the previous iteration.

jayilych4real jayilych4real · Answer 2 · 2021-11-25T12:06:28+01:00

The K-Means algorithm terminates when:_

B. the cluster centers for the current iteration are identical to the cluster centers for the previous iteration.

According to the given question, we are asked to show when the K-Means algorithm terminates and the conditions which must be observed before this happens.

As a result of this, we can see that the K-mean algorithm has to do with dividing and organising k clusters of data which have similarities to each other and are denoted by a centroid.

With this in mind, we can see that the algorithm terminates when the cluster centers for the current iteration are identical to the cluster centers for the previous iteration.

Therefore, the correct answer is option B