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Attribute Relevance Analysis

Attribute Relevance Analysis

Copyright: © 2015 |Pages: 17
ISBN13: 9781466662889|ISBN10: 1466662883|EISBN13: 9781466662896
DOI: 10.4018/978-1-4666-6288-9.ch007
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MLA

Goran Klepac, et al. "Attribute Relevance Analysis." Developing Churn Models Using Data Mining Techniques and Social Network Analysis, IGI Global, 2015, pp.173-189. https://doi.org/10.4018/978-1-4666-6288-9.ch007

APA

G. Klepac, R. Kopal, & L. Mršić (2015). Attribute Relevance Analysis. IGI Global. https://doi.org/10.4018/978-1-4666-6288-9.ch007

Chicago

Goran Klepac, Robert Kopal, and Leo Mršić. "Attribute Relevance Analysis." In Developing Churn Models Using Data Mining Techniques and Social Network Analysis. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6288-9.ch007

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Abstract

Structured problems need to be quantified by relevance, and that is explained in this chapter. The most common methods of relevance analysis and different strength and sensitivity measures are explained in a way that practitioners can easily use them and start experimenting. Contrary to the belief that powerful hardware and sophisticated software can substitute for attribute relevance analysis, attribute relevance analysis is an important part of each analysis that operates with the target variable. Recognition of the most important variables, those with the greatest impact on the target variable, reduces redundancy and uncertainty at the model development process stage. It provides robustness of the model and model reliability. Attribute relevance analysis also evaluates attribute characteristics. Attribute characteristics evaluation includes measuring attribute values' impact on target variables. It helps in understanding relations and logic between the most important predictors and the target variable and understanding relations and logic between the most important predictors from the target variable perspective. Making models relevant and being able to proof them is relevant and almost as important as the ability to build them. After completing this chapter, analysts (readers) are ready to start projects.

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