Automated/Manual Parameters Selection

Pannasoft Ingenuity gives users the flexibility to automatically or manually adjust the network parameters for analyzing data. In auto mode, the efficient learning algorithm will automatically adjust network parameters to find a suitable architecture. In manual mode, the user is able to manually fine-tune the parameters.

Rule Extraction and Pruning Strategy

Pannasoft Ingenuity provides rule explanation capability to gain a wider degree of user acceptance on the results and to let user understand the potential and ability of the trained engine in handling classification problems. Pruning strategy enables user to remove low confidence and unimportant prototypes (knowledge) from the system to reduce complexity and network size.

Retrieve Old Knowledge

Pannasoft Ingenuity enables user to retrieve old prototypes from the database and combine them with new input samples to form new prototypes. Thus, the time used to retrain is significantly reduced.

Multiple Classifier System

Multiple Classifier Systems enable Pannasoft Ingenuity to produce better results and higher accuracy in decision making using a voting system mechanism.

Multiple Jobs

Pannasoft Ingenuity can accommodate different category of data sets (e.g. data on credit card spending, health diagnosis, manufacturing operation and etc) in one database.

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