I have a huge dataset (1.5 million obs and 70 features). I want to visualize the data in 2D, to look for naturally occurring clusters. Analogous to Van der Maaten's approach 1, I first reduce the dimensions to 10 using PCA. Then I apply t-SNE to the dataset where now each obs is represented as a vector of 10 PCA scores.
My question is, while applying t-SNE, do I need to standardize each of the 10 score columns? In MATLAB, the suggestion is :"When features in X are on different scales, set 'Standardize' to true. Do this because the learning process is based on nearest neighbors, so features with large scales can override the contribution of features with small scales." I am not sure if PC scores are on different scales or not. I know that the PC scores, on average fall in value with the PC.