Extracting SVD vectors for LSA
I am trying to perform latent semantic analysis (LSA) of text using SVD. So I can see the SVD vectors in the resulting SVD model, I can play with them, however, there seems no way of extracting them (and now way of gettimg to Eigenvalues either). I know there was a similar post 5 years ago and the recommended solution was to use R instead. Lots of things must have changed since.
Today I can see three possibilities:
- Somehow split the model into its two matrices and access them as examples - at this stage, I cannot see such an operator;
- Get to the weights of SVD components and extract them one by one - Weight by Component Model looked promising but I could not achieve the required result;
- Save the model and read it back as XML - seemed like an idea but the XML seems very complex and I cannot find the required bits to easily read them in as vectors or examples.
Any ideas to do this in pure RapidMiner - apart from the R solution which at this stage seems the simplest?