An overview of the use of neural networks for data mining tasks
Citations Over TimeTop 10% of 2012 papers
Abstract
Abstract In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically‐inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc. This article is categorized under: Technologies > Classification Technologies > Computational Intelligence Technologies > Prediction Technologies > Structure Discovery and Clustering
Related Papers
- → Which side are you on?(2006)272 cited
- → Building Better Workplaces through Individual Perspective Taking: A Fresh Look at a Fundamental Human Process(2008)113 cited
- Perspective Drawing : A Step-by-Step Handbook(1990)
- → Results Perspective One : Network Perspective(2013)
- Creative perspective for artists and designers(1995)