I would like to ask if somebody can help me with the following problem. I would like to generate synthetic data for dimension reduction algorithm testing. Specifically, I would like to have for example a matrix with 1000 rows (=points) and 50 columns (=features) but the real dimension of such matrix after dimension reduction should have only 10 features. How can I generate such matrix? I prefer python code but any advice helps me.

I found out that I can multiply a random matrix (with 1000 rows and 10 columns) by the transposed first matrix from SVD decomposition (with 10 rows and 50 columns) but I do not know why.


Your Answer

By clicking "Post Your Answer", you acknowledge that you have read our updated terms of service, privacy policy and cookie policy, and that your continued use of the website is subject to these policies.

Browse other questions tagged or ask your own question.