I have a data set of size (4600, 10000). I did L2 normalization at first, then I did the following two steps to visualize it in a lower dimension:
1: Performed SVD and obtain 60 components, then performed PCA and obtain 30 components then did t-SNE on these 30 PCA components and obtain 2 components for visualization 2: Did PCA and obtain 50 components, then performed t-SNE and obtain 2 components for visualization.
The visualization from the first step is more clear than the second one. Does it make sense to do so? I all of these modules from scikit-learn.