  We consider the dynamic classifier selection (DCS) problem: Given an ensemble
of classifiers, we are to choose which classifier to use depending on the
particular input vector that we get to classify. The problem is a special case
of the general algorithm selection problem where we have multiple different
algorithms we can employ to process a given input. We investigate if a method
developed for general algorithm selection named cost-sensitive hierarchical
clustering (CSHC) is suited for DCS. We introduce some additions to the
original CSHC method for the special case of choosing a classification
algorithm and evaluate their impact on performance. We then compare with a
number of state-of-the-art dynamic classifier selection methods. Our
experimental results show that our modified CSHC algorithm compares favorably
