Here we choose to apply the resubstitution method and the holdout method. 472-479, July 1974. We will thus resort to estimating this error, or rather its average over all possible training sets of a given size N . Consider for example the second option. 5.3 Estimation of Misclassification A most important and still too often neglected problem in pattern recognition concerns the proper experimental methodology for estimating the performance of a decision rule.
Many geometric problems occur here as well where computational geometry offers solutions.
IT-20, July 1974, pp. 5.3 Estimation of Misclassification A most important and too often neglected problem in computer vision concerns the proper experimental methodology for estimating the performance of a decision rule. Many geometric problems occur here as well. IT-20, July 1974, pp. No context found.