Metric learning for monotonic classification: turning the space up to the limits of monotonicity
Juan Luis Suárez,
Germán González-Almagro,
Salvador García
et al.
Abstract:This paper presents, for the first time, a distance metric learning algorithm for monotonic classification. Monotonic datasets arise in many real-world applications, where there exist order relations in the input and output variables, and the outputs corresponding to ordered pairs of inputs are also expected to be ordered. Monotonic classification can be addressed through several distance-based classifiers that are able to respect the monotonicity constraints of the data. The performance of distance-based clas… Show more
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