One of the editors, Teuvo Kohonen, first developed the concept of SOMs beginning in the early 1980s. He has pursued the expansion and exploitation of this technique extensively.
SOMs are a fundamental branch of neural network theory.
With SOMs, the learning algorithms are unsupervised. The user supplies data, and the SOM algorithm searches for clusters using nonlinear procedures. The perspective of this book, showing a spectrum of examples combined with theory, portrays the power of SOMs to solve real financial problems where unsupervised learning is necessary. SOMs are demonstrated to often be more effective than classical clustering algorithms. While clustering techniques often have very restrictive assumptions or limited ability to find complex shapes, SOMs are much more able to isolate clusters in high dimensional space, particularly those clusters that are not tight little balls of data but rather twisting, curving regions of N-space.