An Experimental comparison of fixed and trained fusion rules for crisp classifiers outputs

at present, fixed rules for classifier combination are the most used and widely investigated ones, while the study and application of trained rules has received much less attention. Therefore , pros and cons of fixed and traibned rules are only partially known even if one focuses on crisp classifiers outputs. in this paper , we report the results of an xperimaìental comparison of well-known fixed and trained rules for crisps classifirìers outputs, reported experiments allow one draw some preliminary conclusions about comparative advantages of fixed and trained fusion rules