Showing 1 - 7 of 7
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/10009789907
Persistent link: https://www.econbiz.de/10009789908
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
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
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/10008560052