Simple Graphs for Complex Prediction FunctionsSimple Graphs for Complex Prediction Functions
- Other Titles
- Simple Graphs for Complex Prediction Functions
- Authors
- 허명회; 이용구
- Issue Date
- 2008
- Publisher
- 한국통계학회
- Keywords
- Visualization; prediction function; LOESS; neural network model; supportvector machine; random forest.
- Citation
- Communications for Statistical Applications and Methods, v.15, no.3, pp.343 - 351
- Indexed
- KCI
- Journal Title
- Communications for Statistical Applications and Methods
- Volume
- 15
- Number
- 3
- Start Page
- 343
- End Page
- 351
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/124900
- ISSN
- 2287-7843
- Abstract
- By supervised learning with p predictors, we frequently obtain a prediction func-tion of the formy = f(x1;:;x p). When p 3, it is not easy to understand theinner structure off, except for the case the function is formulated as additive. Inthis study, we propose to usep simple graphs for visual understanding of com-plex prediction functions produced by several supervised learning engines such asLOESS, neural networks, support vector machines and random forests.
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Collections - College of Political Science & Economics > Department of Statistics > 1. Journal Articles
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