In this paper, a leave-one-out cross-validation based PRESS criterion is first presented for model selection of MR to choose appropriate regularization ...
model selection of manifold regularization based on minimization of the leave- one-out cross-validation criteria of the model selection, which can be performed.
This paper is concerned with model selection of manifold regularization based on the minimization of leave-one-out cross-validation criteria, which is extended ...
In this paper, a leave-one-out cross-validation based PRESS criterion is first presented for model selection of MR to choose appropriate regularization ...
A simple and efficient approach to model selection for weighted least-squares support vector machines, and compares a variety of model selection criteria ...
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A gradient approach to the optimization of hyper-parameters which is based on the closed form for the generalized cross validation estimate is proposed, ...
The manifold regularization (MR) based semi-supervised learning could explore structural relationships from both labeled and unlabeled data.
Feb 13, 2019 · To address this problem, in this paper, we present a novel approximate approach to CV for model selection of mani- fold regularization based on ...
Leave-One-Out cross-validation based model selection for manifold regularization. ISNN'10: Proceedings of the 7th international conference on Advances in ...
If using Leave-One-Out cross-validation, alphas must be strictly positive. fit_interceptbool, default=True. Whether to calculate the intercept for this model.