MCR-Miner: Maximal Confident Association Rules Miner Algorithm for Up/Down-Expressed Genes
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چکیده
منابع مشابه
MCR-Miner: Maximal Confident Association Rules Miner Algorithm for Up/Down-Expressed Genes
DNA microarrays allow simultaneous measurements of expression levels for a large number of genes across a number of different experimental conditions (samples). The algorithms for mining association rules are used to reveal biologically relevant associations between different genes under different experimental samples. This paper presents a new column-enumeration based method algorithm (abbrevi...
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Building a high accuracy classifier for classification is a problem in real applications. One high accuracy classifier used for this purpose is based on association rules. In the past, some researches showed that classification based on association rules (or class-association rules – CARs) has higher accuracy than that of other rule-based methods, such as ILA and C4.5. However, mining CARs cons...
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Data mining methodology has a tremendous contribution for extracting the hidden knowledge and patterns from the existing databases. Traditionally, researchers use basket data to mine association rules of which the basic task is to find the frequent items. For relational databases whose data format is relational data other than basket data, RDB-MINER algorithm was proposed. In this paper, we int...
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In this study, a new classification technique based on rough set theory and MEPAR-miner algorithm for association rule mining is introduced. Proposed method is called as ‘Reduced MEPAR-miner Algorithm’. In the method being improved rough sets are used in the preprocessing stage in order to reduce the dimensionality of the feature space and improved MEPAR-miner algorithms are then used to extrac...
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Discovering causal relations in a system is essential to understanding how it works and to learning how to control the behaviour of the system. RFCT is a causality miner that uses association relations as the basis for the discovery of causal relations. It does so by making explicit the temporal relationships among the data. RFCT uses C4.5 as its association discoverer, and by using a series of...
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ژورنال
عنوان ژورنال: Applied Mathematics & Information Sciences
سال: 2014
ISSN: 1935-0090,2325-0399
DOI: 10.12785/amis/080241