Proactive Data Mining with Decision Trees

Released on by Haim Dahan
preview-18

  • Proactive Data Mining with Decision Trees Book Detail

  • Author : Haim Dahan
  • Release Date : 2014-02-14
  • Publisher : Springer Science & Business Media
  • Genre : Computers
  • Pages : 94
  • ISBN 13 : 1493905392
  • File Size : 68,68 MB
DOWNLOAD BOOK

Proactive Data Mining with Decision Trees by Haim Dahan PDF Summary

Book Description: This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.

Disclaimer: www.yourbookbest.com does not own Proactive Data Mining with Decision Trees books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Proactive Data Mining with Decision Trees

Proactive Data Mining with Decision Trees

File Size : 23,23 MB
Total View : 3295 Views
DOWNLOAD

This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predi