Title :
An integrated data preparation scheme for neural network data analysis
Author :
Yu, Lean ; Wang, Shouyang ; Lai, K.K.
Author_Institution :
Dept. of Manage. Sci., City Univ. of Hong Kong, China
Abstract :
Data preparation is an important and critical step in neural network modeling for complex data analysis and it has a huge impact on the success of a wide variety of complex data analysis tasks, such as data mining and knowledge discovery. Although data preparation in neural network data analysis is important, some existing literature about the neural network data preparation are scattered, and there is no systematic study about data preparation for neural network data analysis. In this study, we first propose an integrated data preparation scheme as a systematic study for neural network data analysis. In the integrated scheme, a survey of data preparation, focusing on problems with the data and corresponding processing techniques, is then provided. Meantime, some intelligent data preparation solution to some important issues and dilemmas with the integrated scheme are discussed in detail. Subsequently, a cost-benefit analysis framework for this integrated scheme is presented to analyze the effect of data preparation on complex data analysis. Finally, a typical example of complex data analysis from the financial domain is provided in order to show the application of data preparation techniques and to demonstrate the impact of data preparation on complex data analysis.
Keywords :
cost-benefit analysis; data analysis; data mining; neural nets; cost-benefit analysis framework; data mining; integrated data preparation scheme; intelligent data preparation; knowledge discovery; neural network data analysis; neural network data preparation; Artificial intelligence; Artificial neural networks; Biological neural networks; Cost benefit analysis; Data acquisition; Data analysis; Data mining; Mathematical model; Neural networks; Scattering; Index Terms- Data preparation; complex data analysis; cost-benefit analysis.; neural networks;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2006.22