GP Classification under Imbalanced Data sets: Active Sub-sampling and AUC Approximation


The problem of evolving binary classification models under increasingly unbalanced data sets is approached by proposing a strategy consisting of two components: Sub-sampling and ‘robust’ fitness function design. In particular, recent work in the wider machine learning literature has recognized that maintaining the original distribution of exemplars during… (More)
DOI: 10.1007/978-3-540-78671-9_23


4 Figures and Tables


Citations per Year

55 Citations

Semantic Scholar estimates that this publication has 55 citations based on the available data.

See our FAQ for additional information.

Slides referencing similar topics