Confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine
• No confidence and prediction intervals have been derived yet for mixed effect LS-SVM. • We derive analytical formulas for quantifying uncertainty for mixed effect LS-SVM. • Derived formulas closely match results from the wild cluster bootstrap-t procedure.
Autor*in: |
Cheng, Qiang [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2014 |
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Schlagwörter: |
Least squares support vector machine |
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Umfang: |
8 |
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Übergeordnetes Werk: |
Enthalten in: Thermal structure optimization of a supercondcuting cavity vertical test cryostat - Jin, Shufeng ELSEVIER, 2019, an official publ. of the International Association for Pattern Recognition, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:40 ; year:2014 ; day:15 ; month:04 ; pages:88-95 ; extent:8 |
Links: |
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DOI / URN: |
10.1016/j.patrec.2013.12.010 |
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ELV027880125 |
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Confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine |
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• No confidence and prediction intervals have been derived yet for mixed effect LS-SVM. • We derive analytical formulas for quantifying uncertainty for mixed effect LS-SVM. • Derived formulas closely match results from the wild cluster bootstrap-t procedure. |
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• No confidence and prediction intervals have been derived yet for mixed effect LS-SVM. • We derive analytical formulas for quantifying uncertainty for mixed effect LS-SVM. • Derived formulas closely match results from the wild cluster bootstrap-t procedure. |
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• No confidence and prediction intervals have been derived yet for mixed effect LS-SVM. • We derive analytical formulas for quantifying uncertainty for mixed effect LS-SVM. • Derived formulas closely match results from the wild cluster bootstrap-t procedure. |
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