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Decision Tree Pruning Using Expert Knowledge

  • Kartonierter Einband
  • 236 Seiten
Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. How to prune the de... Weiterlesen
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Beschreibung

Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. How to prune the decision tree is one of the research directions of the decision tree technique, but the idea of cost-sensitive pruning has received much less attention than other pruning techniques even though additional flexibility and increased performance can be obtained from this method. This dissertation reports on a study of cost-sensitive methods for decision tree pruning. A decision tree pruning algorithm called KBP1.0, which includes four cost-sensitive methods, is developed. The intelligent inexact classification is used for first time in KBP1.0 to prune the decision tree. Using expert knowledge in decision tree pruning is discussed for the first time. By comparing the cost-sensitive pruning methods in KBP1.0 with other traditional pruning methods on benchmark data sets, the advantage and disadvantage of cost-sensitive methods in KBP1.0 have been summarized. This research will enhance our understanding of the theory, design and implementation of decision tree pruning using expert knowledge.

Produktinformationen

Titel: Decision Tree Pruning Using Expert Knowledge
Untertitel: Cost-sensitive Pruning
Autor:
EAN: 9783836491556
ISBN: 978-3-8364-9155-6
Format: Kartonierter Einband
Genre: Informatik
Anzahl Seiten: 236
Gewicht: 330g
Größe: H12mm x B220mm x T150mm
Jahr: 2013