The scatterplot matrix can inform you about the conjoint distributions of your features. It helps you locate groups in data and verify whether they are distinguishable. Parallel coordinates are another kind of plot that is helpful in providing you with a hint about the most group-discriminating variables present in your data.
By plotting all the observations as parallel lines with respect to all the possible variables (arbitrarily aligned on the abscissa), parallel coordinates will help you spot whether there are streams of observations grouped as your classes, and understand the variables that best separate the streams (the most useful predictor variables). Naturally, in order for the chart to ...
