What is a good way to visualize high dimensional (say n=10) binary data? I remember reading something about that a few years ago.
Say for instance, you want to plot / cluster pizzas based on their topping, e.g. ham, chicken, mushrooms etc.
Even if this is binary, you can do a scaled Principal Component Analysis (PCA). By projecting the results on the 2D plane of the first Principal Components you get an idea of the clustering of your data.
# data is your data.frame/matrix of data pca <- prcomp(data, scale.=TRUE) # Screeplot to see how much variance is in the 2D plane plot(pca) # Projections plot(data %*% pca$rotation[,1:2])
Sometimes for binary data Parallel Coordinate Plots can work quite well (you will stil have to play around with it, but it would work much better than with non-binary data).