Improved Predictive Clustering Tree Algorithm with Post Pruning Hierarchical Multi-Label Classification
-
- Englisch ausgewählt
Fr. 224.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
09.12.2014
Verlag
LAP LAMBERT Academic PublishingSeitenzahl
96
Maße (L/B/H)
22/15/0.7 cm
Gewicht
161 g
Sprache
Englisch
ISBN
978-3-659-24272-4
Multi label classification is a variation of single label classification problem where each instance is associated with more than one class label. The foremost unremarkably used approach to handle multi-label classification problem is to transfer multi-label problem into single label problems, where binary classifier is learned independently for every attainable class labels. However, multi-labeled data generally exhibit relationships between labels, but multi-label classification approach fails to take such relationships under consideration. It's understood that in this type of classification, labels co-relationship should be maintain. Label co-relationships can be visualized either in tree structure hierarchies or in DAG (Directed Acyclic Graph) structure hierarchies. These hierarchical arrangement of labels maintain the hierarchical constraint that is once an instance belongs to some class that automatically belongs to all its super classes. This book presents several variations to the induction of decision tree using Predictive Clustering Tree (PCT) algorithm for Hierarchical Multi-label Classification.
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.