Selective inductive transfer
Beau Piccart, Jan Struyf, Hendrik Blockeel · Lirias · 2008
Multi-target models, which predict multiple target variables simultaneously, may predict some of the targets more accurately, and other targets less accurately than a single-target model. This raises the question whether it is possible to find, for a given main target, a subset of the other targets that, when combined with the main target in a multi-target model, results in the most accurate model for the main target. We propose Selective Inductive Transfer, an algorithm that automatically finds such a subset.