SCOPUS 정보 검색 플랫폼

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5271 LNAI, Issue , 2008, Pages 466-474

An EM-based piecewise linear regression algorithm

(3) Nusser, Sebastian a,b Otte, Clemens a Hauptmann, Werner a

a SIEMENS AG (Germany)

b OTTO VON GUERICKE UNIVERSITY (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BENCH-MARK PROBLEMS; INPUT SPACE; LOCAL REGRESSION MODELS; MODEL COMPLEXITY; PIECEWISE LINEAR REGRESSION; PIECEWISE REGRESSION; PREDICTIVE PERFORMANCE; PROTOTYPE SELECTION; REGRESSION METHOD;

ARTIFICIAL INTELLIGENCE; PIECEWISE LINEAR TECHNIQUES;

REGRESSION ANALYSIS;

EID: 70350540442 PISSN: 03029743 EISSN: 16113349 Source Type: Book Series
DOI: 10.1007/978-3-540-87656-4_58 Document Type: Conference Paper

Times cited : (3)

References (7)

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- Ritter, H.¹

2
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- Hathaway, R.J.¹ Bezdek, J.C.²

3
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- A new learning method for piecewise linear regression
- Springer, Heidelberg
- Ferrari-Trecate, G., Muselli, M.: A new learning method for piecewise linear regression. In: Proc. of International Conference on Artificial Neural Networks, pp. 444-449. Springer, Heidelberg (2002)
- (2002) Proc. of International Conference on Artificial Neural Networks , pp. 444-449
- Ferrari-Trecate, G.¹ Muselli, M.²

4
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- Improved fuzzy partitions for fuzzy regression models
- Höppner, F., Klawonn, F.: Improved fuzzy partitions for fuzzy regression models. International Journal of Approximate Reasoning 32(2-3), 85-102 (2003)
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- Höppner, F.¹ Klawonn, F.²

5
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- Maximum likelihood from incomplete data via the EM algorithm
- Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society. Series B 39(1), 1-38 (1977)
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- Dempster, A.P.¹ Laird, N.M.² Rubin, D.B.³

6
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- Learning binary classifiers for applications in safetyrelated domains
- Universitätsverlag Karlsruhe, pp
- Nusser, S., Otte, C., Hauptmann, W.: Learning binary classifiers for applications in safetyrelated domains. In: Proc. of 17th Workshop Computational Intelligence, Universitätsverlag Karlsruhe, pp. 139-151 (2007)
- (2007) Proc. of 17th Workshop Computational Intelligence , pp. 139-151
- Nusser, S.¹ Otte, C.² Hauptmann, W.³

7
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- Wrappers for feature subset selection
- Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence 97(1-2), 273-324 (1997)
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.