Support Vector Regression with Interval-Input Interval-Output
Support vector machines (classification and regression) are powerful machine learning techniques for crisp data. In this paper, the problem is considered for interval data. Two methods to deal with the problem using support vector regression are proposed and two new methods for evaluating performanc...
Ausführliche Beschreibung
Autor*in: |
Wensen An [verfasserIn] Cecilio Angulo [verfasserIn] Yanguang Sun [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2008 |
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Übergeordnetes Werk: |
In: International Journal of Computational Intelligence Systems - Springer, 2017, 1(2008), 4 |
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Übergeordnetes Werk: |
volume:1 ; year:2008 ; number:4 |
Links: |
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DOI / URN: |
10.2991/ijcis.2008.1.4.2 |
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Katalog-ID: |
DOAJ043008380 |
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Support vector machines (classification and regression) are powerful machine learning techniques for crisp data. In this paper, the problem is considered for interval data. Two methods to deal with the problem using support vector regression are proposed and two new methods for evaluating performance for estimating prediction interval are presented as well. |
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