Weighted discriminant embedding: Discriminant subspace learning for imbalanced medical data classification

Tobey H. Ko, Zhonglei Gu, Yang LIU

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

A model designed for automatic prediction of diseases based on multimedia data collected in hospitals is introduced in this working notes paper. In order to perform the automatic diseases prediction efficiently, while using as few data as possible for training, we develop a two-stage learning strategy, which first performs the weighted discriminant embedding (WDE) to project the original data to a low-dimensional feature subspace and then utilizes the cost-sensitive nearest neighbor (CS-NN) method in the learned subspace for disease prediction. The proposed approach is evaluated on the MediaEval 2018 Medico Multimedia Task. Copyright held by the owner/author(s).

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume2283
Publication statusPublished - 2018
Event2018 Working Notes Proceedings of the MediaEval Workshop, MediaEval 2018 - Sophia Antipolis, France
Duration: 29 Oct 201831 Oct 2018

Scopus Subject Areas

  • Computer Science(all)

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