A decision cognizant Kullback-Leibler divergence

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A decision cognizant Kullback-Leibler divergence

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作者：Moacir Ponti^a ; ^b ; ^{ponti@usp.br" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Josef Kittler^b ; ^{j.kittler@surrey.ac.uk" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Mateus Riva^a ; ^{mateusriva@usp.br" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Teó ; filo de Campos^b ; ^c ; ^{t.decampos@st-annes.oxon.org" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Cemre Zor^b ; ^{c.zor@surrey.ac.uk" class="auth_mail" title="E-mail the corresponding author}Author Vitae
关键词：Kullback&ndash ; Leibler divergence ; Divergence clutter ; Classifier incongruence
刊名：Pattern Recognition
出版年：2017
出版时间：January 2017
年：2017
卷：61
期：Complete
页码：470-478
全文大小：2692 K

文摘

•: The decision cognizant Kullback–Leibler divergence is a better statistic to measure classifier (in)congruence.
•: Analytic and simulation studies show the new divergence is more robust to minority class clutter.
•: Sensitivity to estimation error is lower than that of the classical Kullback–Leibler divergence.

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