Ensemble of Classifiers Based on Association Rule Mining

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Provided by: International Journal of Advanced Research in Computer Engineering & Technology
Topic: Data Management
Format: PDF
In data mining, classification is the process of finding and applying a model to describe and distinguish data classes, concepts and values. The model that is built is called a classifier or predictor depending upon whether the model finds the unknown data class or data value. Single classifier may not be very much accurate; ensemble systems use an \"Ensemble\" or group of classifiers to improve the accuracy. Associative classification is an approach in data mining that utilizes the association rule discovery techniques to build classification systems, also known as associative classifiers.
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