- I have 50 text documents
- There are 500 possible words, after a stop list has been applied
- My term/document sparse matrix is therefore 50x500
I'd like to cluster these documents. One easy way to do this would be via k-means but that requires giving each document co-ordinates on a 2-d graph.
I've heard that I can reduce the 500-word long vectors per document using dimensionality reduction, specifically PCA.
Is it realistic that I could just reduce my 50x500 matrix to a 50x2 table and plot those values?