We present a novel ensemble pruning method based on reordering the classifiers obtained from bagging and then selecting a subset for aggregation. Ordering the classifiers generate...
In this paper, a new variant of Bagging named DepenBag is proposed. This algorithm obtains bootstrap samples at first. Then, it employs a causal discoverer to induce from each sam...
Yuan Jiang, Jinjiang Ling, Gang Li, Honghua Dai, Z...
The performance of m-out-of-n bagging with and without replacement in terms of the sampling ratio (m/n) is analyzed. Standard bagging uses resampling with replacement to generate ...
—This paper describes an evolutionary music composition system that combines trainable music critics with a bag of notes constraint. Unlike many evolutionary composition systems,...
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...