Скачать или смотреть s-CorrPlot

Project Page: http://mckennapsean.com/projects/s-co...

The degree of correlation between variables is used in many data analysis applications as a key measure of interdependence. The most common techniques for exploratory analysis of pairwise correlation in multivariate datasets, like scatterplot matrices and clustered heatmaps, however, do not scale well to large datasets, either computationally or visually. We present a new visualization that is capable of encoding pairwise correlation between hundreds of thousands variables, called the s-CorrPlot. The s-CorrPlot is based on a 2D scatterplot and exploits the geometric structure underlying Pearson’s correlation to derive a novel spatial encoding. We implemented the s-CorrPlot as an open-source proof of concept visualization in order to validate its effectiveness through a variety of methods including a case study with a biology collaborator.