Improved Multidimensional Scaling Analysis Using Neural Networks with Distance-Error Backpropagation
Luís Garrido, Sergio Gómez, Jaume Roca · Neural Computation · 1999
We show that neural networks, with a suitable error function for backpropagation, can be successfully used for metric multidimensional scaling (MDS) (i.e., dimensional reduction while trying to preserve the original distances between patterns) and are in fact able to outdo the standard algebraic approach to MDS, known as classical scaling.