The quest of the best classifier for a discriminant analysis problem is often rather hard and a combination of classifiers of different type promises to lead to improved predictive models compared to selecting one of the competitors. We propose to use the out-of-bag sample for training of...

The combination of classifiers leads to substantial reduction of misclassification error in a wide range of applications and benchmark problems. We suggest to use the out-of-bag sample for combining different classifiers. In our setup, a Linear Discriminant Analysis is performed using the...