Stacked regression with restrictions

• Autorzy: Tomasz Górecki
• Języki publikacji: EN

Abstrakty

EN

When we apply stacked regression to classification we need only discriminant indices which can be negative. In many situations, we want these indices to be positive, e.g., if we want to use them to count posterior probabilities, when we want to use stacked regression to combining classification. In such situation, we have to use leastsquares regression under the constraint βₖ ≥ 0, k = 1,2,...,K. In their earlier work [5], LeBlanc and Tibshirani used an algorithm given in [4]. However, in this paper we use a more general algorithm given in [6].

Słowa kluczowe

EN

stacked regression; regression with restrictions; mixed regression

Kategorie tematyczne

• 62J05: Linear regression
• 62H30: Classification and discrimination; cluster analysis

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2005
• Tom: 25
• Numer: 1
• Strony: 103-113

Daty

wydano

2005

otrzymano

2005-03-02

Twórcy

autor

Tomasz Górecki

• Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614 Poznań, Poland

Bibliografia

• [1] C. Blake and C. Merz, UCI Repository of Machine Learning Databases, http://www.ics.uci.edu/ mlearn/MLRepository.html, Univeristy of California, Irvine, Department of Information and Computer Sciences.
• [2] L. Breiman, Stacked Regression, Machine Learning 24 (1996), 49-64.
• [3] A. Chaturvedi and A. Wan, Estimation of Regression Coefficients Subject to Interval Constraints in Models with Non-spherical Errors, Snakhy[`a] 61 series B (1999), 433-442.
• [4] J. Lawson and R. Hanson, Solving Least Squares Problems, Prentice-Hall, New Jersey 1974.
• [5] M. LeBlanc and R. Tibshirani, Combining Estimates in Regression and Classification, JASA 91 (1996), 1641-1650.
• [6] H. Toutenburg and B. Roeder, Minimax-Linear and Theil Estimator forRestricted Regression Coefficients, Statistics 9 (1978), 499-505.
• [7] D. Wolpert, Stacked Generalization, Neural Networks 5 (1992), 241-259.

Identyfikatory

DOI

10.7151/dmps.1064