machine learning - Conclusion from PCA of dataset -


i have set of data sequence labeling. did pca (with 2 principal components on x , y axis) on dataset , turns out below: pca of raw dataset

using lstm network classify dataset above, decided extract activations hidden layer of lstm. obtain figure below: pca of activation lstm hidden layer using above dataset

my question is, conclusion can draw comparing both results? fair features of original dataset self-organized after running through lstm classifier?


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