PBC4cip: A new contrast pattern-based classifier for class imbalance problems
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- 作者：Octavio Loyola-Gonzá ; lez ; a ; b ; octavioloyola@inaoep.mx" class="auth_mail" title="E-mail the corresponding author ; octavioloyola@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Miguel Angel Medina-Pé ; rezc ; migue@itesm.mx" class="auth_mail" title="E-mail the corresponding author ; José ; Fco. Martí ; nez-Trinidada ; fmartine@inaoep.mx" class="auth_mail" title="E-mail the corresponding author ; Jesú ; s Ariel Carrasco-Ochoaa ; ariel@inaoep.mx" class="auth_mail" title="E-mail the corresponding author ; Raú ; l Monroyc ; raul@itesm.mx" class="auth_mail" title="E-mail the corresponding author ; Milton Garcí ; a-Borrotod ; mgarciab@ceis.cujae.edu.cu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Supervised classifier ; Contrast patterns ; Imbalanced databases
- 刊名：Knowledge-Based Systems
- 出版年：2017
- 出版时间：1 January 2017
- 年：2017
- 卷：115
- 期：Complete
- 页码：100-109
- 全文大小：744 K
文摘
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A new contrast pattern-based classifier for class imbalance problems is introduced.
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PBC4cip is based on the support of the patterns and the class imbalance level.
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PBC4cip outperforms several classifiers designed for class imbalance problems.