How not to reduce dimensionality for clustering
In my previous post, I followed up on my k-means tutorial by applying it to cluster MNIST. We’re used to reading digits, so the centroids made perfect sense to us since plotting them just looked like a smudged number. The dataset even clustered pretty well since all digits are centred and look similar enough that […]
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