Proactive Data Mining with Decision Trees

Haim Dahan, Shahar Cohen, Lior Rokach, Oded Maimon

Research output: Book/ReportBookpeer-review

Abstract

In the previous chapter we introduced the task of proactive data mining and sketched an algorithmic framework for solving the task: first build a prediction model and then use it for optimization. In this chapter, we focus on decision tree classifiers and describe in detail two possible ways of implementing proactive data mining using: (a) a ready-made decision tree algorithm, and (b) a novel decision tree algorithm. We designed this latter algorithm to support the optimization phase of the proposed framework.
Original languageEnglish
PublisherSpringer
Number of pages88
ISBN (Print)978-1-4939-0538-6, 978-1-4939-0539-3
DOIs
StatePublished - 2014

Publication series

NameSpringer Briefs in Electrical and Computer Engineering

Fingerprint

Dive into the research topics of 'Proactive Data Mining with Decision Trees'. Together they form a unique fingerprint.

Cite this