2013
DOI: 10.5120/12153-8126
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Relational Classification using Multiple View Approach with Voting

Abstract: Classification is an important task in data mining and machine learning, in which a model is generated based on training dataset and that model is used to predict class label of unknown dataset. Various algorithms have been proposed to build accurate and scalable classifiers in data mining. These algorithms are only applied to single table. Today most realworld data are stored in relational format which is popular format for structured data which consist of tables connected via relations (primary key/ foreign … Show more

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Cited by 6 publications
(2 citation statements)
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“…In a follow-up meta-comparison we compared our achieved results on the financial task with those of some prominent techniques for multi-relational classification problems. We considered here the propositionalization methods DARA [27], RELAGGS [35], and CrossMine [19], as well as the multi-view approaches MVC [43] and MRC [20]. Table III shows the predictive accuracies of each representative.…”
Section: Meta-comparisonmentioning
confidence: 99%
“…In a follow-up meta-comparison we compared our achieved results on the financial task with those of some prominent techniques for multi-relational classification problems. We considered here the propositionalization methods DARA [27], RELAGGS [35], and CrossMine [19], as well as the multi-view approaches MVC [43] and MRC [20]. Table III shows the predictive accuracies of each representative.…”
Section: Meta-comparisonmentioning
confidence: 99%
“…Zhen et al[208] propose a two-stage algorithm which is based on semisupervised classification to address the different distribution problem in cross-domain classification. Also, another perspective is relational classification[100,138,212] used in text classification, which could boost the overall performance greatly.…”
mentioning
confidence: 99%