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Proactive Data Mining with Decision TreesProactive Data Mining: A General Approach and Algorithmic Framework

Proactive Data Mining with Decision Trees: Proactive Data Mining: A General Approach and... [In the previous section we presented several important data mining concepts. In this chapter, we argue that with many state-of-the-art methods in data mining, the overly-complex responsibility of deciding on this action or that is left to the human operator. We suggest a new data mining task, proactive data mining. This approach is based on supervised learning, but focuses on actions and optimization, rather than on extracting accurate patterns. We present an algorithmic framework for tackling the new task. We begin this chapter by describing our notation.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Proactive Data Mining with Decision TreesProactive Data Mining: A General Approach and Algorithmic Framework

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References (6)

Publisher
Springer New York
Copyright
© The Author(s) 2014
ISBN
978-1-4939-0538-6
Pages
15 –20
DOI
10.1007/978-1-4939-0539-3_2
Publisher site
See Chapter on Publisher Site

Abstract

[In the previous section we presented several important data mining concepts. In this chapter, we argue that with many state-of-the-art methods in data mining, the overly-complex responsibility of deciding on this action or that is left to the human operator. We suggest a new data mining task, proactive data mining. This approach is based on supervised learning, but focuses on actions and optimization, rather than on extracting accurate patterns. We present an algorithmic framework for tackling the new task. We begin this chapter by describing our notation.]

Published: Feb 15, 2014

Keywords: Proactive data mining; Domain knowledge

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