Boosting multiple experts by joint optimisation of decision thresholds
Josef Kittler, Yusseri Yusoff, William J. Christmas, Terry Windeatt, David Windridge · Surrey Research Insight Open Access (The University of Surrey) · 2001
We consider a multiple classifier system which combines the hard decisions of experts by voting. We argue that the individual experts should not set their own decision thresholds. The respective thresholds should be selected jointly as this will allow compensation of the weaknesses of some experts by the relative strengths of the others. We perform the joint optimization of decision thresholds for a multiple expert system by a systematic sampling of the multidimensional decision threshold space. We show the effectiveness of this approach on the important practical application of video shot cut detection.