Noisy multi-label semi-supervised dimensionality reduction

作者：

Highlights：

• A new semi-supervised and label noise-tolerant multi-label dimensionality reduction method.

• Based on label propagation for noisy multi-labels and dependence maximization.

• A novel framework for semi-supervised classification of noisy multi-label data.

• A case study of patients suffering from multiple chronic diseases.

摘要

•A new semi-supervised and label noise-tolerant multi-label dimensionality reduction method.•Based on label propagation for noisy multi-labels and dependence maximization.•A novel framework for semi-supervised classification of noisy multi-label data.•A case study of patients suffering from multiple chronic diseases.

论文关键词：Label noise,Multi-label learning,Semi-supervised learning,Dimensionality reduction

论文评审过程：Received 18 September 2018, Revised 21 December 2018, Accepted 25 January 2019, Available online 29 January 2019, Version of Record 5 February 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.01.033