Original paper
3D fast convex-hull-based evolutionary multiobjective optimization algorithm
Abstract
The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves have been widely used in the machine learning community to analyze the performance of classifiers. The area (or volume) under the convex hull has been used as a scalar indicator for the performance of a set of classifiers in ROC and DET space. Recently, 3D convex-hull-based evolutionary multiobjective optimization algorithm (3DCH-EMOA) has been proposed to...
Paper Details
Title
3D fast convex-hull-based evolutionary multiobjective optimization algorithm
Published Date
Jun 1, 2018
Journal
Volume
67
Pages
322 - 336
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Notes
History