I far what i understand, the assumptions for PCA is that data should be linear.
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?
How do we check if the data is linear or not?
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?