In my last post, I talked about why SAS utilizes a rotated Singular Value Decomposition (SVD) approach for topic generation, rather than using Latent Dirichlet Allocation (LDA). I noted that LDA has undergone a variety of improvements in the last seven years since SAS opted to use the SVD method. So, the
There's a sense of foreboding and uncertainty. You look around, but you're uncertain where to go next. What to do. Or who to turn to. Ultimately, it feels like an eerie calm before the storm. And you get that creepy feeling that something awful is just around the corner. I might be
When you work with big data, you often deal with both a large number of observations and a large number of features. When the number of features is large, they can be highly correlated, resulting in significant amount of redundancy in the data. Principal component analysis can be a very
