Add to ORKGAbstract. We show how to implement the cross-validation technique used in ma-chine learning as a slice model. We describe the formulation in terms of support vector machines and extend the GAMS/DEA interface to allow for ecient solu-tions of linear, mixed integer and simple quadratic slice models under GAMS.
5 pages, 6 figures. Contribution to the proceedings of the 17th International workshop on Advanced C...
Data validation describes the process of checking the internal consistency, correctness and quality ...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
© 1989-2012 IEEE. As machine learning systems become democratized, it becomes increasingly important...
This paper presents a theory of error in cross-validation testing of algorithms for predicting real-...
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
In this paper we investigate cross validation and Geisser’s sample reuse approaches for designing li...
The learning using privileged information paradigm has allowed support vector machine models to inco...
We propose a fast, incremental algorithm for designing linear regression models. The proposed algori...
Branch-and-Bound algorithm is the basis for the majority of solving methods in mixed integer linear ...
Semiparametric models are useful tools in the case where domain knowledge exists about the function ...
In this paper the training of Least Squares Support Vector Machines (LS-SVMs) for classification and...
In many applications, optimization of a collection of problems is required where each problem is str...
Predictions from each split of cross-validation, generating cross-validated estimates for each input...
5 pages, 6 figures. Contribution to the proceedings of the 17th International workshop on Advanced C...
Data validation describes the process of checking the internal consistency, correctness and quality ...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
© 1989-2012 IEEE. As machine learning systems become democratized, it becomes increasingly important...
This paper presents a theory of error in cross-validation testing of algorithms for predicting real-...
<p>The data set is partitioned into 10 parts (folds) in the outer loop. One fold of the data set is ...
In this paper we investigate cross validation and Geisser’s sample reuse approaches for designing li...
The learning using privileged information paradigm has allowed support vector machine models to inco...
We propose a fast, incremental algorithm for designing linear regression models. The proposed algori...
Branch-and-Bound algorithm is the basis for the majority of solving methods in mixed integer linear ...
Semiparametric models are useful tools in the case where domain knowledge exists about the function ...
In this paper the training of Least Squares Support Vector Machines (LS-SVMs) for classification and...
In many applications, optimization of a collection of problems is required where each problem is str...
Predictions from each split of cross-validation, generating cross-validated estimates for each input...
5 pages, 6 figures. Contribution to the proceedings of the 17th International workshop on Advanced C...
Data validation describes the process of checking the internal consistency, correctness and quality ...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p