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= Changes
== Multi-shot Classification The system is designed to get the most out of one-shot training data. We explain in the discussion that there is a natural extension to multi-shot training data. However we don't provide much more explanation nor an evaluation of the performances.
-> Explain in details how the algorithm work with multiple training samples per class. Explain that this is a competitive system where samples of the same class compete against each other but play for the same team. There may be a change to make on the computation of the threshold that should only consider distances between different classes (min of distance between two samples of different classes, this has a specific name in hierarchical clustering design). Provide an evaluation in the case where a pattern can have multiple modes.