The HNeT Supervised Learning (SL) Platform is an assembly generation tool structured for feed-forward supervised learning.  Developers can load standard ASCII or binary files containing stimulus-response training, testing and validation data.  Optimization of assembly performance may be performed in a fully automated manner.  Generated assemblies may be deployed through the HNet Application Programming Interface.

Automation tools facilitate assembly generation using the SL Platform executable as a local or remote server, allowing the analyst to allocate a server farm across an array of networked computers.  These automation tools allow the analyst to centrally batch process SL Platform project files, and provide a central monitoring/analysis facility for the entire SL Platform server farm.

Numerous utilities are provided in this environment, such as performance testing, graphical analysis aids, data preparation wizards, etc.  Data files may be segmented into training, testing, and validation sets for automated performance optimization and verification.  Work sessions may be saved as projects, whereby all related data files, assembly configurations and program settings are managed by the system and reloaded through a click of a button.  Various screen views of the HNeT SL Platform are shown to the left.