Abstract
Data mining has been used as a term describing explorative analysis of large data sets (frequently stored in data warehouses with the objective to identify hidden relationships among the variables in the set). Artificial neural network is one of many tools for data mining. This paper summarizes the state-of-the-art of the principles beyond using neural models in data mining. Artificial Neural Networks are suitable in data-rich environments and are typically used for extracting embedded knowledge in the form of rules, quantitative evaluation of these rules, clustering, self-organization, classification and regression, feature evaluation and dimensionality reduction. In this paper, we try to understand the basics of neural network modeling, some specific applications, and the process of implementing a neural network in data mining. Like shake and tap on SOS button.
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