Figure 12

Graph of changes in ACC as a function of Δ m , Δ n , Δ M and Δ N when decision trees are used as a classifier a) and graph of changes in ACC as a function of Δ m for each level of the decision tree cutting b)- this is the second compared method (method 2). Changes (graph a) in the position and size of the ROI affect to an increasing extent the dynamics of changes in ACC. For the basic setting Δm=Δn=ΔM=ΔN=0, ACC is equal to 84%. The further from the basic setting 0 pixels, the higher the dynamics of changes in ACC becomes. The value of the level 0 (graph b) means no tree pruning. Trees are pruned based on an optimal pruning scheme that first pruned branches give less improvement in error cost. For most of the created decision trees, changes in ACC are in the range of 5%. When decision trees are cut too much, they lose their ability of correct classification. Such a situation is visible in the chart below (level 6) where ACC changes from 85% to 55%.