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I didn't notice it mentioned but what's the Big-Oh performance of the sub-optimal k-means clustering algorithm? O(k)?
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The complexity of the sub-optimal (!) k-means algorithm is typically very high (e.g. it's NP-hard).
That's actually why I've used the number of algorithm optimizations such as k-means++ initialization algorithm, thoroughly discussed in this article, as well as the ability of the initialization process to produce the number of initial clusters prior to performing the actual clustering, and that really helps to reduce the computational complexity of the k-means algorithm.
Why not a simple title, like "Classifying Data Using Artificial Intelligence"? And maybe the blurb can be something like, "A simple introduction to using K-Means Clustering for data analysis," or something like that. Then make the first paragraph about types of data and use cases, to draw the reader in to how to do it with K-Means Clustering. No need to scare your users by using big words in the title. The current title tells me it is going to be technical and non-user friendly except for possibly those who are already knowledgeable in the field.
You talk about what and how; but you don't say "why" this subject should be of interest. You need a "hook" to grab the readers' attention … early. Think of something in real life the audience can relate to and how your article / topic relates.
It was only in wine that he laid down no limit for himself, but he did not allow himself to be confused by it.
― Confucian Analects: Rules of Confucius about his food
I edited your subject line - let's keep "rude words" off the homepage, eh? Particularly when they look like something designed to start a flame war if the fanboise don't even follow the link or watch the video (like I didn't and I don't own any apple products) ...
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