Single- vs. multiple-instance classification

作者：

Highlights：

• We categorize problems by the amount of label information instances in a bag carry.

• We define synthetic tasks of increasing complexity or intra-bag dependency.

• These problems allow us to measure the power of multiple-instance algorithms.

• We experiment on two bioinformatics data for gene expression and text categorization.

摘要

Highlights•We categorize problems by the amount of label information instances in a bag carry.•We define synthetic tasks of increasing complexity or intra-bag dependency.•These problems allow us to measure the power of multiple-instance algorithms.•We experiment on two bioinformatics data for gene expression and text categorization.

论文关键词：Classification,Multiple-instance learning,Similarity-based representation,Bioinformatics

论文评审过程：Received 1 September 2014, Revised 16 February 2015, Accepted 3 April 2015, Available online 16 April 2015, Version of Record 16 May 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.04.006