A neuro-fuzzy method to learn fuzzy classification rules from data
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Towards Process-Oriented Tool Support for Knowledge Discovery in Databases
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
SPIDA — A Novel Data Analysis Tool
BT Technology Journal
Fuzzy trust evaluation and credibility development in multi-agent systems
Applied Soft Computing
An ANN embedded RTS smoother for an INS/GPS integrated Positioning and Orientation System
Applied Soft Computing
A novel self-adaptive clustering algorithm for dynamic data
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
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Data analysis tools are still very much a collection of data analysis methods that require analysis experts as users. On the other hand, many business users are keen to apply data analysis to business data in order to understand it or to make predictions to improve on their business decisions. In order to make state-of-the-art data analysis techniques available to such non-experts, we developed a wizard for our data analysis tool SPIDA that selects appropriate data analysis methods given soft high-level requirements. The wizard also configures and runs the chosen methods automatically. This paper describes our general approach to automating data analysis, in particular, how to select an appropriate data analysis algorithm.