Suppose we have a multi-class classification problem, where the number of classes $K \geq 3$
We use a tree structure of multiple SVMs to divide and conquer the problem, with one example in the figure below.
Generally, in this kind of hierarchical classification, if a sample is wrongly classified in an upper layer, it is less likely to be corrected again in lower layers.
My question: Is there any strategy to mitigate such hierarchical error propagation in tree-structured classification?
Much appreciated!
