Showing 1 - 8 of 8
We describe a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing Bohachevsky et al (1986) is used to solve this problem. The classification error is determined by an exact integration. We avoid distance or scatter...
Persistent link: https://www.econbiz.de/10010982337
In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expected error rates in multivariate classification.
Persistent link: https://www.econbiz.de/10010982366
We propose a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing (Bohachevsky et al 1986) as a modern optimization technique is used to solve this problem effectively. This approach easily allows to incorporate user...
Persistent link: https://www.econbiz.de/10010982395
We propose multivariate classification as a statistical tool to describe business cycles. These cycles are often analyzed as a univariate phenomenon in terms of GNP or industrial net production ignoring additional information in other economic variables. Multivariate classification overcomes...
Persistent link: https://www.econbiz.de/10010982396
In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expected error rates in multivariate classification.
Persistent link: https://www.econbiz.de/10010316538
We propose a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing (Bohachevsky et al 1986) as a modern optimization technique is used to solve this problem effectively. This approach easily allows to incorporate user...
Persistent link: https://www.econbiz.de/10010316563
We propose multivariate classification as a statistical tool to describe business cycles. These cycles are often analyzed as a univariate phenomenon in terms of GNP or industrial net production ignoring additional information in other economic variables. Multivariate classification overcomes...
Persistent link: https://www.econbiz.de/10010316572
We describe a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing Bohachevsky et al (1986) is used to solve this problem. The classification error is determined by an exact integration. We avoid distance or scatter...
Persistent link: https://www.econbiz.de/10010316665