메뉴 건너뛰기
Library Notice
Institutional Access
If you certify, you can access the articles for free.
Check out your institutions.
ex)Hankuk University, Nuri Motors
Log in Register Help KOR
Subject
Humanities
General Humanities History Philosophy Religious Studies Linguistics and Literature Other Humanities
Social science
General Social Science Business Management Tourism Education Military Science Library and Information Science Law Sociology Journalism and Media Studies Psychological Science Political Science and Diplomacy Geography Public Administration Economics International Trade Anthropology Other Social Science
Natural science
General Natural Science Physics Biology Life Sciences Mathematics/Statistics Astronomy Earth Science Chemistry Other Natural Science
Engineering
General Engineering Architectural Engineering Mechanical Engineering Industrial Engineering Material/Energy Engineering Electrical and Electronic Engineering Marine and Ocean Engineering Chemical Engineering Computer Science Other Engineering
Medical science
General Medical Science Nursing Science Veterinary Pharmacy Traditional Korean Medicine Basic Medicine Clinical Medicine Other Medicine
Agriculture and Fishery
General Agriculture and Fishery Agriculture Fishery Science Food Science Forestry Animal Husbandry Marine Transportation Studies Other Agriculture and Fishery
Art and Kinesiology
General Arts Design Fine Arts Cosmetology Photography Music Fashion Kinesiology Performing Media Arts Other Arts and Kinesiology
Interdisciplinary Studies
Interdisciplinary Research Science and Technology Studies Brain and Cognitive Science Technology Policy Other Interdisciplinary Studies

KOR

Impact of Ensemble Member Size on Confidence-based Selection in Bankruptcy Prediction
Recommendations
Search
Questions

논문 기본 정보

Type
Academic journal
Author
Na-Ra Kim (Ewha Womans University) Kyung-Shik Shin (Ewha Womans University) Hyunchul Ahn (Kookmin University)
Journal
Korea Intelligent Information Systems Society Journal of Intelligence and Information Systems Vol.19 No.2 KCI Accredited Journals
Published
2013.6
Pages
55 - 71 (17page)

Usage

cover
📌
Topic
📖
Background
🔬
Method
🏆
Result
Impact of Ensemble Member Size on Confidence-based Selection in Bankruptcy Prediction
Ask AI
Recommendations
Search
Questions

Abstract· Keywords

Report Errors
The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.
#부도예측 #앙상블 #결합기법

Contents

1. Introduction
2. Review of Related Studies
3. Research Methodology
4. Model Development
5. Experiments
6. Concllusions
References
Abstract

References (51)

Add References
1. [학술대회논문] - Abdelwahed, T. / 2005 / New Evolutionary Bankruptcy Forecasting Model based on Genetic Algorithms and Neural Networks / Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence google schola 2. [학술지(정기간행물)] - Alfaro, E. / 2008 / Bankruptcy forecasting : an empirical comparison of AdaBoost and neural networks / Decision Support Systems 45 : 110 ~ 122 google schola 3. [학술지(정기간행물)] - Altman, E. I. / 1968 / Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy / The Journal of Finance 23 (4) : 589 ~ 609 google schola 4. [학술지(정기간행물)] - Atiya, A. F. / 2001 / Bankruptcy Prediction for Credit Risk Using Neural Networks : A Survey and New Results / IEEE transactions on neural networks 12 (4) : 929 ~ 935 google schola 5. [학술지(정기간행물)] - Back, B. / 1996 / Neural networks and genetic algorithms for bankruptcy predictions / Expert Systems with Applications 11 : 407 ~ 413 google schola

Related Authors

Frequently Viewed Together

Post Processing Algorithm Proposal of Platform Game Artificial Intelligence for A* Path Planning Application
HyunTae Kim ,  KyungJoong Kim 한국정보과학회 학술발표논문집 2013 .11
A Study on Types and Limitations of Control Systems in Computer Game Artificial Intelligence
Sun-Joon Yu Journal of Digital Contents Society 2006 .03
A Study on the Image Search System using Mobile Internet
Eunjee Song Journal of Digital Contents Society 2011 .06
HSM(Hierarchical State Machine) based LOD AI for Computer GamesS
Jinseok Seo Journal of Digital Contents Society 2013 .06
Applications of Machine Learning for Games: Case Studies
Hyunsoo Pa ,  k ,  DuMim Yoon and others 2 대한전자공학회 학술대회 2013 .07

Recently viewed articles

Experiences and Perception of Young Adults and Their Parent Generation Regarding Young Adults’ Parent-Dependent Cohabiting
Kim, Hye Eun, Jung 외 7명Korean Association of Human Ecology2021.12

Comments(0)

0

Write first comments.

UCI(KEPA) : I410-ECN-0101-2014-000-003172513