Implementing an idea of visualizing the classification problems (with real-valued attributes) as heatmaps. Each row, in this heatmap is an attribute, where columns correspond to the classes to be classified.
A good benefit of this approach of multidimensional visualization is that it color-codes (or exposes) key variations of different attributes (columns) over the classes (rows) and allows the individual to decide about which attribute should be more focused, while classifying the data.
For the sake of visuals, an implementation is done on popular IRIS dataset.