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This paper lies within the domain of learning algorithms based on kernels of Support Vector Machines. A kernel is constructed over the discrete structure of absolute orders of magnitude spaces. This kernel is based on an explicit function, defined from the space of k-tuples of qualitative labels to a feature space, which captures the remoteness between the(More)
This paper offers a new method inspired by classic importance-performance analysis (IPA) that provides a global index of importance versus performance for firms together with a new version of the IPA diagram. The index compares two rankings of the same set of features regarding importance and performance, taking into account under-performing features. The(More)