Improving Accuracy of Decision Trees Using Clustering Techniques

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Provided by: Journal of Universal Computer Science
Topic: Big Data
Format: PDF
Data mining is an important part of information management technology. Simply put, it is a method to extract and analyze meaningful patterns and correlations in a large relational database. In data mining, decision trees are one of the most worldwide used tools for decision support. In the emerging area of data mining applications, users of data mining tools are faced with the problem of data sets that are comprised of large numbers of features and instances. Such kinds of data sets are not easy to handle for mining because decision trees generally depends on several parameters like dataset used and configuration of the tree itself among others in order to build an accurate model classification.
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