New Features of SNNSv4.0

Version 4.0 of SNNS features the following improvements and extensions over the earlier version 3.3:

A new distributed version of the kernel. SNNS can now be spread out in a workstation cluster for faster learning.
Improved version of the C-code generator snns2c
Validation sets now can check on the performance of the network during training.
New error function in tool analyze that can handle single-output-unit-networks.
New statistic tool that can predict the generalization capabilities of the network.
Reorganization of the manager panel with new selection mechanism for the major SNNS windows.
The remote panel was changed significantly and renamed `control panel'.
Selection possibility in the graph panel between plot of SSE, MSE, and SSE/output.
New learning algorithm RBF\_DDA
New learning algorithm simulated annealing
New learning algorithm Monte Carlo.
New learning algorithm Pruned-Cascade-Correlation
Several new initialization algorithms for Kohonen and Counterpropagation networks, since the two old ones had serious flaws.
Key codes to bring up all the main panels of SNNS (e.g Alt-c for the control panel).
Support for NeXT systems.
More information printed to the shell during training and with the INFO button.
The SOURCE and TARGET part of the info panel have been swapped for a more intuitive setup of the information.
Extensive debugging (as usual).

Last modified: mache@rembrandt Thu May 18 15:11:32 MET DST 1995