Automated Test Procedure

[wboler05]

Currently, we are running various tests by hand, which is becoming tedious as expected. To further our progress, a complex automated test procedure should be implemented that can automatically generate tests based on the accuracy of the overall best ANN. This test procedure should smartly choose which datasets to use, based on independent tests of separate LOAs. It should also implement smart ANN selection, which determines the best ANN for a given set of inputs from topological training enabled, and then disabling topological training with the desired generated topology. Once deciding on an ANN, input values should be tweaked for determining which data provides the best accuracy, and then further training and validation should commence on the new selection.

For further consideration, it may need to be able to isolate nodes with minimal degree (or some metric) to determine which nodes to drop for continuation of training.

A possible implementation would require for a configuration file to be created which contains the location of all files separated LOAs, and a possible schedule.

[wboler05]

Need an input dialog that asks the user whether to proceed with next test, skip, or stop all training.

[wboler05]

Need to modify current implementation to contain a list of input files to read. Need to modify how the net adjusts the topology based on the result from the previous result.