SOMinterpreted
SOMinterpreted is a term that can refer to various interpretations or applications of Self-Organizing Maps (SOMs). SOMs are a type of artificial neural network that uses unsupervised learning to produce a low-dimensional discretized representation of the input space of the training samples, called a map. This map is topologically ordered, meaning that similar input samples are mapped to similar locations on the map.
One common interpretation of SOMinterpreted relates to the analysis of complex datasets. Researchers might use SOMs
Another interpretation involves using SOMs for feature extraction. The neurons on the SOM grid can be seen
Furthermore, SOMinterpreted can refer to the post-processing and analysis of the trained SOM itself. This might