I far what i understand, the assumptions for PCA is that data should be linear.

  1. What does that imply? let say if i have a data of 1000*100. So all independent variables should be linearly separable with dependent variable? Can anyone please explain this?

  2. How do we check if the data is linear or not?

  3. PCA is a linear transformation method and t-SNE is non linear transformation method. What is the difference between both specifically in terms of linearity?


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