Since any modification of a Self-Organizing Map in the 2D display like
the creation, deletion or movement of units or weights may destroy the
relative position of the units in the map we strongly recommend to
generate these networks only with the available BIGNET (Kohonen)
tool. See also chapter 
for detailed information on how
to create networks. Outside xgui you can also use the tool
convert2snns. Information on this program can be found in the
respective README file in the directory SNNSv3.3/tools/doc. Note: Any
modification of the units after the creation of the network may result
in undesired behavior!
To train a new feature map with SNNS, set the appropriate standard
functions: select init function KOHONEN_Weights, update
function Kohonen_Order and learning function Kohonen.
Remember: There is no special activation function for Kohonen
learning, since setting an activation function for the units doesn't
affect the learning procedure. To visualize the results of the
training, however, one of the two activation functions
Act_Euclid and Act_Componnent has to be selected. For their
semantics see section .
After providing patterns (ideally normalized) and assigning reasonable values to the learning function, the learning process can be started. To get a proper appearance of SOMs in the 2D-display set the grid width to 16 and turn off the unit labeling and link display in the display panel.
When a learning run is completed the adaption height and adaption radius parameters are automatically updated in the remote panel to reflect the actual values in the kernel.