Supervised learning: It induces an input-output mapping from a data set, called learning data set. It is usually limited to a MISO (multiple input single output) system. The learning data set includes items.
Some items may activate the rules with a low matching degree. An item
will be considered as inactive if its maximum matching degree over all
rules is lower than a user chosen threshold (default value=
0.1. Inactive items are not managed by the FIS.
The number of inactive items is used to define a coverage index,
calculated as follows:
A is the number of active items and n the number
of rows in the data file.
Performance indices, calculated from the active examples only.
For a classification case:
where equa;s 1 for a misclassified item, 0 otherwise.
For a regression case, three indices are available:
is the historical accuracy index used by previous versions of
FisPro, RMSE is the Root Mean Squared Error, et
MAE is the Mean Absolute Error.