A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection Export

@inproceedings{citeulike:531106, abstract = {We review accuracy estimation methods and compare the two most common methods: crossvalidation and bootstrap. Recent experimental results on artificial data and theoretical results in restricted settings have shown that for selecting a good classifier from a set of classifiers (model selection), ten-fold cross-validation may be better than the more expensive leaveone -out cross-validation. We report on a largescale experiment---over half a million runs of C4.5 and a Naive-Bayes algorithm---to...}, author = {Kohavi, Ron}, booktitle = {IJCAI}, citeulike-article-id = {531106}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.529}, pages = {1137--1145}, posted-at = {2006-11-23 00:49:46}, priority = {2}, title = {A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.529}, year = {1995} }

TY - CONF ID - citeulike:531106 L3 - citeulike-article-id:531106 N2 - We review accuracy estimation methods and compare the two most common methods: crossvalidation and bootstrap. Recent experimental results on artificial data and theoretical results in restricted settings have shown that for selecting a good classifier from a set of classifiers (model selection), ten-fold cross-validation may be better than the more expensive leaveone -out cross-validation. We report on a largescale experiment---over half a million runs of C4.5 and a Naive-Bayes algorithm---to... EP - 1145 TI - A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection T2 - IJCAI SP - 1137 AU - Kohavi, Ron PY - 1995/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.529 ER -