Dear all,
when learning a BN from data, some algorithms (such as K2) are influenced by the variable order. And if this initial order is not the most appropriated, the results may be prejudiced. Trying to find this best order may be an exponential problem (when it's done by exhaustive search). One way to minimize this problem may be to prune the "less" significant variables. I've already implemented some initial tests and they showed that it's worthwhile to look for the best order when trying to improve the learning results. So I was wondering if there is any defined heuristic to deal with this problem. Thank you so much for your attention. Estevam. - -_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_- Estevam Rafael Hruschka Junior [EMAIL PROTECTED] Curitiba PR. - Brazil.
