Abstract
This chapter presents two real world implementations of the proactive data mining, using decision trees from two different sectors: cellular services (Sect. 4.1) and security (Sect. 4.2). Using actual datasets, we address real problems that two companies in these business areas face.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arbel R, Rokach L (2006) Classifier evaluation under limited resources. Pattern Recogn Lett 27(14):1619–1631
Feigenbaum E A (1989) Toward the library of the future. Long Range Plann 22(1):118–123
Hung S-Y, Yen DC, Wang H-Y (2006) Applying data mining to telecom churn management. Expert Syst Appl 31:515–524
Matatov N, Rokach L, Maimon O (2010) Privacy-preserving data mining: a feature set partitioning approach. Inform Sci 180(14):2696–2720
Menahem E, Rokach L, Elovici Y (2009) Troika–an improved stacking schema for classification tasks. Inform Sci 179(24):4097–4122
Rokach L, Maimon O, Lavi I (2003) Space decomposition in data mining: a clustering approach. Found Intell Syst 24–31
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 The Author(s)
About this chapter
Cite this chapter
Dahan, H., Cohen, S., Rokach, L., Maimon, O. (2014). Proactive Data Mining in the Real World: Case Studies. In: Proactive Data Mining with Decision Trees. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0539-3_4
Download citation
DOI: https://doi.org/10.1007/978-1-4939-0539-3_4
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-0538-6
Online ISBN: 978-1-4939-0539-3
eBook Packages: Computer ScienceComputer Science (R0)