How deeply does Cyber Threat Hunting cover k-means++ initialization?

Mentions k-means++ only as a variation and defers its mechanics to further study.

K-means++ initialization

K-means++ is an initialization method that selects well-spaced initial centroids for the k-means algorithm.

K-means++ is an initialization method for k-means that selects well-spaced starting centroids. It is one of several k-means variations to consider when choosing a clustering approach for a problem. section 8.8

Choose clustering algorithms according to the problem, and try more than one when exploring data. Careful data processing and parameter tuning remain important because clustering can assign data points incorrectly. section 8.8

How Cyber Threat Hunting covers it

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