Visualization of Large Data Sets Using MDS Combined with LVQ
Antoine Naud, Włodzisław Duch · 2003
A common task in data mining is the visualization of multivariate objects using various methods, allowing human observers to perceive subtle inter-relations in the dataset. Multidimensional scaling (MDS) is a well known technique used for this purpose, but it due to its computational complexity there are limitations on the number of objects that can be displayed. Combining MDS with a clustering method as Learning Vector Quantization allows to obtain displays of large databases that preserve both high accuracy of clustering methods and good visualization properties. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.