Two choices are available. With the first one (default one), a clustering is performed using the rule conclusions, with the second one it is done by using the data file output values. The clustered values are chosen as the new rule conclusions.
The number of distinct conclusions can be set, or the tolerated loss of performance. Indeed reducing the voabulary usually goes with a loss of accuracy.
FIS menu, Reduce the output vocabulary option.
Command line, vocreduc program:
|-oNumOutput where NumOutput is the output number (default: 0=first output)|
| -dType data used to make vocabulary reduction
|-lPerfLoss: PerfLoss is the relative performance loss allowed by vocabulary reduction (default: 0.1)|
| -cConc: Conc is the number of elements in the reduced vocabulary (default: 10000).
Remark: these 2 argument default values are 0.1 for PerfLoss, which yields an automatic determination of Conc.
|-sMuMin where MuMin is the activity threshold for an item not to be blank (default: 0.2)|
|-a: detailed output|
Command line example
vocreduc rice.fis rice
The number of conclusions passes from 25 to 6.