48 citations · 49 across the 3 of their papers we have counts for
3 papers · 1 filter
Multi-objective Clustering: A Data-driven Analysis of MOCLE, MOCK and -MOCK
Adriano Kultzak, Cristina Y. Morimoto, Aurora Pozo +1
We present a data-driven analysis of MOCK, -MOCK, and MOCLE. These are three closely related approaches that use multi-objective optimization for crisp clustering. More specific…
Quantifying With Only Positive Training Data
Denis dos Reis, Marcílio de Souto, Elaine de Sousa +1
Quantification is the research field that studies methods for counting the number of data points that belong to each class in an unlabeled sample. Traditionally, researchers in thi…
How Complex is your classification problem? A survey on measuring classification complexity
Ana C. Lorena, Luís P. F. Garcia, Jens Lehmann +2
Characteristics extracted from the training datasets of classification problems have proven to be effective predictors in a number of meta-analyses. Among them, measures of classif…