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Standard Additive Model in Data Mining

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3 Author(s)
Do-Thanh Sang ; Dept. of Electron. Eng., Myongji Univ., Yongin, South Korea ; Dong-Min Woo ; Dong-Chul Park

The habitual purpose of data mining is prediction, one of the most direct real-world applications. There are many technologies available to data mining in literature and they achieved some results with reasonable accuracies. This paper designs and implements an advanced model based on fuzzy inference system, namely Standard Additive Model (SAM) for forecasting the output of any record given the input variables only from the database, the age of abalone in particular. SAM offers an optimum solution for the prediction and can be definitely an alternative approach for conventional models such as neural networks. The experimental result comparison to multi-layer perceptron neural network (MLPNN) is provided in same context.

Published in:

Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2010 International Conference on

Date of Conference:

10-12 Oct. 2010