Improved computation of beliefs based on confusion matrix for combining multiple classifiers

One approach among a number of strategies for multiple classifier combination is to calculate the beliefs of confidence based on confusion matrices from individual classifiers. To achieve precise belief computation, based on previous researchers´ work, presented is a better algorithm with a more generic capability, showing improved performance.