I have 50 Matrices of data with 80*80 dimensions. I need to classify them, but before that I have to reduce the dimensionality of data. As I searched the web, the best tool is PCA. I know that before classification I have to transform each Matrix to row vector, But I don't know about PCA. Should I transform Matrices to row vectors and then reduce the dimensionality by PCA or no use PCA for each Matrix with its basic shape?
Asked
Active
Viewed 58 times
0
-
I couldn't find anything related to this question, Could you please give me the related links? – Araz Sep 27 '15 at 06:46
-
You don't have enough samples anyway ... (by a factor of 128) – Lamar Latrell Sep 30 '15 at 03:35