I've been working on a dataset about a few millions commuters and their travel patterns with around 50 dimensions. And I'm applying t-SNE to the dataset.
My initial goal of applying t-SNE was to visually confirm the clustering potential of the dataset, i.e. the presence of natural structures in the dataset. Fortunately, t-SNE consistently outputs 3 distinct clusters in all runs. Even better, the t-SNE clusters make business sense when I plugged the original commuter characteristics in to interpret.
But when I research about the applications of t-SNE, few people seem to discuss about using it as a clustering algorithm (Of course, the clusters need to be assigned with the help of human annotator looking at the t-SNE plots). There are many articles about how to apply t-SNE for data visualization and dimensionality reduction.
Discussion in Clustering on the output of t-SNE dismissed t-SNE as lacking 'a concise, intuitive description of what objective the cluster assignment algorithm minimizes'. Can someone please help elaborate on this comment, and whether it is right to apply t-SNE as a clustering algorithm?