Principal Components in General Line Coordinates for Visualization and Machine Learning

Understanding and visualizing principal components without losing multi-dimensional information has been a long-standing challenge until now. Here, we describe a novel lossless visual technique that overcomes such difficulties, General Line Coordinates-Principal Components Analysis (GLC-PCA)-an approach that provides much more information about individual cases than other methods, with improved structural readability and comprehensibility for PCA. Experimental case studies and comparisons with other works demonstrate this effect. A software system called MAVERICK implements it.