Labeling Emotions in Suicide Notes: Cost-Sensitive Learning with Heterogeneous Features

Jonathon Read; Erik Velldal; Lilja �vrelid

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Biomedical Informatics Insights

Labeling Emotions in Suicide Notes: Cost-Sensitive Learning with Heterogeneous Features

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Jonathon Read, Erik Velldal and Lilja Øvrelid

Biomedical Informatics Insights 2012:5 (Suppl. 1) 99-103

Original Research

Published on 30 Jan 2012

DOI: 10.4137/BII.S8930

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Abstract

This paper describes a system developed for Track 2 of the 2011 Medical NLP Challenge on identifying emotions in suicide notes. Our approach involves learning a collection of one-versus-all classifiers, each deciding whether or not a particular label should be assigned to a given sentence. We explore a variety of features types—syntactic, semantic and surface-oriented. Cost-sensitive learning is used for dealing with the issue of class imbalance in the data.

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