Although activations can be propagated through the network without patterns defined, learning can be performed only with patterns present. A set of patterns belonging to the same task is called a pattern set. Normally there are two dedicated pattern sets when dealing with a neural network. One for training the network (training pattern set), and one for testing purposes to see what the network has learned (test pattern set). In SNNS both of these (and more) can be kept in the simulator at the same time. They are loaded with the file browser (see chapter ). The pattern set loaded last is made the current pattern set. All actions performed with the simulator refer only to, and affect only the current pattern set. To switch between pattern sets press the button in the control panel (see figure on page ). It opens up a list of loaded pattern sets from which a new one can be selected. The name of the current pattern set is displayed to the right of the button. The name equals the name body of the loaded pattern file. If no pattern set is loaded, ``Patternfile ?'' is given as indication that no associated pattern file is defined.
Loaded pattern sets can be removed from main memory with the button in the control panel. Just like the button it opens a list of loaded pattern sets, from which any set can be deleted. When a pattern set is deleted, the corresponding memory is freed, and again available for other uses. This is especially important with larger pattern sets, where memory might get scarce.