Estimating Replicability of Classifier Learning Experiments Export

@misc{citeulike:247900, abstract = {Replicability of machine learning experiments measures how likely it is that the outcome of one experiment is repeated when performed with a di\#erent randomization of the data. In this paper, we present an estimator of replicability of an experiment that is e\#cient. More precisely, the estimator is unbiased and has lowest variance in the class of estimators formed by a linear combination of outcomes of experiments on a given data set.}, author = {Remco, Remco B.}, citeulike-article-id = {247900}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.6734}, keywords = {replicability}, posted-at = {2005-07-06 16:53:29}, priority = {4}, title = {Estimating Replicability of Classifier Learning Experiments}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.6734} }

TY - GEN ID - citeulike:247900 L3 - citeulike-article-id:247900 N2 - Replicability of machine learning experiments measures how likely it is that the outcome of one experiment is repeated when performed with a di#erent randomization of the data. In this paper, we present an estimator of replicability of an experiment that is e#cient. More precisely, the estimator is unbiased and has lowest variance in the class of estimators formed by a linear combination of outcomes of experiments on a given data set. TI - Estimating Replicability of Classifier Learning Experiments KW - replicability AU - Remco, Remco UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.6734 ER -