Evaluation Criteria for Multi-label Classification
Date Issued
2007
Date
2007
Author(s)
Fan, Rong-En
DOI
en-US
Abstract
Multi-label classification becomes more and more popular in recent years. It is used in, for example, text categorization or multimedia retrieval systems. Many evaluation criteria are proposed for different application needs. A commonly used approach for multi-label classification is the binary method, which constructs a decision function per label. For some applications, adjusting thresholds in decision functions improves the performance. This thesis gives a comprehensive
study on the selection of thresholds. Experiments on several
real-world data sets demonstrate the usefulness of some simple selection strategies.
Subjects
多標籤分類
評分標準
門檻值選擇
雙類比對
支撐向量機
multi-label classification
evaluation criteria
supervised threshold setting
binary method
support vector machines
Type
thesis
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