この商品を友人に教える:
Improved Predictive Clustering Tree Algorithm with Post Pruning Thakkar Amit
遠隔倉庫からの取り寄せ
Improved Predictive Clustering Tree Algorithm with Post Pruning
Thakkar Amit
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.
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2014年12月9日 |
| ISBN13 | 9783659242724 |
| 出版社 | LAP Lambert Academic Publishing |
| ページ数 | 96 |
| 寸法 | 6 × 152 × 229 mm · 161 g |
| 言語 | ドイツ語 |