A theory of cross-validation error

A Theory of Cross-Validation Error

This paper presents a theory of error in cross-validation testing of algorithms for predicting real-valued attributes. The theory justifies the claim that predicting real-valued attributes requires balancing the conflicting demands of simplicity and accuracy. Furthermore , the theory indicates precisely how these conflicting demands must be balanced, in order to minimize cross-validation error....

Error rate estimation via cross-validation and learning curve theory

Cross-linguistic Validation of Processability Theory: The Case of EFL Iranian Students’ Speaking Skill

Abstract This study investigated the validity of processability theory proposed by Pienemann (1998/2015) among Iranian EFL learners’ oral performance. The theory defines six procedural stages for learners in the process of second language acquisition. In order to conduct the study, 10 intermediate EFL learners were selected based on their performance on Oxford Placement Test. Then, they partici...

Cross-linguistic Validation of Processability Theory: The Case of EFL Iranian Students’ Speaking Skill

Abstract This study investigated the validity of processability theory proposed by Pienemann (1998/2015) among Iranian EFL learners’ oral performance. The theory defines six procedural stages for learners in the process of second language acquisition. In order to conduct the study, 10 intermediate EFL learners were selected based on their performance on Oxford Placement Test. Then, they partici...

Efficient Algorithms for Minimizing Cross Validation Error

Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected to best predict future data. In some situations, such as online learning for control of robots or factories, data is cheap and human expertise costly. Cross validation can then be a highly effective method for automat...