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I'm working on a classification (3 classes) of unbalanced weather data having 22 features. Even after applying PCA and t-SNE the data is overlapping. The best classification score achieved so far is using the tree-based method. What can be the reason for such PCA plot and what techniques I can implement to get more than 80% accuracy? pca ploty-sne plot

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    $\begingroup$ It could be that your features are not terribly predictive of the outcome. Worth reading… $\endgroup$
    – Dave
    Oct 26, 2021 at 0:19

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I would recommend to use UMAP. It is a superior algorithm to both of them:

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