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Python for Bioinformatics by Kinser

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18 Self-Organizing Maps

The k-means algorithm does a fairly good job of organizing data, but as seen in the previous chapter it does not always provide the best results. A more powerful solution is the self-organizing map (SOM), a data organization algorithm that creates a mapping space that can be used as either a clustering tool or an associative memory (Kohonen 1982, 1990). This chapter will review the construction of the SOM with a simple application.

18.1 SOM Theory

The SOM is a set of vectors arranged in a lattice. The elements of the vectors are altered through training so that the boundaries are created within the lattice. These boundaries define the cluster regions.

The process begins with a set of data vectors that all have the length ...

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