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Cluster analysis is the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors and/or cluster-samples should be tagged as such; do NOT use the "clustering" tag for them.]

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Why is t-SNE not used as a dimensionality reduction technique for clustering or classification?

dimensional data, such as in this answer, yet given the distinct clusters it produces, why is it not used as a dimensionality reduction technique that is then used for classification models or as a standalone clustering
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