In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expected error rates in multivariate classification.

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...

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...

In this paper, control variates are proposed to speed up Monte Carlo simulations to estimate expected error rates in multivariate classification.

In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expected error rates in multivariate classification.

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...