TREE-STRUCTURED APPROACHES AND RECENT ADVANCES
-
- Sugimoto Tomoyuki
- Department of Biomedical Statistics, Graduate School of Medicine, Osaka University
-
- Simokawa Toshio
- Graduate School of Medicine and Engineering, University of Yamanashi
-
- Goto Masashi
- Biostatistical Research Association, NPO
Bibliographic Information
- Other Title
-
- 樹木構造接近法と最近の発展
- ジュモク コウゾウ セッキンホウ ト サイキン ノ ハッテン
Search this article
Abstract
In this article, we review main tree-structured approaches with their recent advances. CART methodology is fundamental and unavoidable in understanding and developing a variety of treestructured approaches. In particular, MARS method provides a useful expansion to the continuous model of CART. In recent advances, some methods developed via combining with ensemble learning method obtain more powerful prediction performance and provide more attractive variable importance. For applied researchers, we present the illustration of applications and a small scale simulation in main tree-structured approaches. Finally, we summarize characteristics of methods and provide some works of interest in the future.
Journal
-
- Bulletin of the Computational Statistics of Japan
-
Bulletin of the Computational Statistics of Japan 18 (2), 123-164, 2007
Japanese Society of Computational Statistics
- Tweet
Details 詳細情報について
-
- CRID
- 1390001204380785920
-
- NII Article ID
- 110006242640
- 10031106362
-
- NII Book ID
- AN10195854
-
- ISSN
- 21899789
- 09148930
-
- NDL BIB ID
- 8780178
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed
