Question

which of the following is required by k-means clustering?(multiple answers)
a)Number of clusters
b)final features used must all be numeric
c)supervised learning algorithm​

Answer 1

Answer:

a) Number of clusters

Explanation:

please mark as brinist list

Answer 2

Answer:

The correct answer to the given question is:

a) Number of clusters

Explanation:

K-means clustering is an unsupervised learning algorithm used to solve clustering problems in machine learning or data science. Group untagged datasets into different clusters. where K determines the number of predefined clusters that will be created in the process. For example, if K=2 there are 2 clusters, if K=3 there are 3 clusters, and so on. This allows you to group your data into different groups and is a convenient way to discover group categories on your own in untagged datasets without training.

Centroid-based algorithm where each cluster is associated with a centroid. The main goal of this algorithm is to minimize the sum of distances between data points and their clusters.

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