Retraction Note to: Mass classification method in mammograms using correlated association rule mining
نویسندگان
چکیده
منابع مشابه
CorClass: Correlated Association Rule Mining for Classification
A novel algorithm, CorClass, that integrates association rule mining with classification, is presented. It first discovers all correlated association rules (adapting a technique by Morishita and Sese) and then applies the discovered rule sets to classify unseen data. The key advantage of CorClass, as compared to other techniques for associative classification, is that CorClass directly finds th...
متن کاملMammogram Classification Using Association Rule Mining
Breast cancer is the primary and the most common disease found among women. It is responsible for rapid growth in mortality rate among all types of cancers in women. Today, mammography the most powerful screening technique is used for early detection of cancer which increases the chance of successful treatment. Screening with mammography can show changes in the breast up to 2-3years before a ph...
متن کاملHybrid Rule Ordering in Classification Association Rule Mining
Classification Association Rule Mining (CARM) is an approach to classifier generation that builds an Association Rule Mining based classifier using Classification Association Rules (CARs). Regardless of which particular CARM algorithm is used, a similar set of CARs is always generated from data, and a classifier is usually presented as an ordered list of CARs, based on a selected rule ordering ...
متن کاملA Novel Rule Ordering Approach in Classification Association Rule Mining
A Classification Association Rule (CAR), a common type of mined knowledge in Data Mining, describes an implicative co-occurring relationship between a set of binary-valued data-attributes (items) and a pre-defined class, expressed in the form of an “antecedent ⇒ consequent-class” rule. Classification Association Rule Mining (CARM) is a recent Classification Rule Mining (CRM) approach that build...
متن کاملIntegrating Classification and Association Rule Mining
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target of discovery is not pre-determined, while for classification rule mining there is one and only one pre...
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ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2015
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-015-2084-8