Sentence examples for error generalization from inspiring English sources

It considers the training error, generalization ability, and distribution of all the training data in the ELM space simultaneously.

This is done by estimating the prediction error (generalization error) on new data and is referred to as model assessment [4].

(a) Error(G): generalization error; (b) AUC G): area under the ROC curve; (c) MCC G Matthewsws correlation coefficient.

Given a gene expression data set D, a set of candidate genes G, and the kNN classifier, the three performance measures of binary classification are denoted by (a) Error(G ): generalization error; (b) AUC G ): area under the ROC curve; (c) MCC G Matthewsews correlation coefficient.

The generalization error (Error) is an intuitive judgment about the misclassification rate, but might not present a valid picture if the two classes under consideration strongly differ in size.

These characteristics enable to approximate complex functions with a generally low generalization error.

Data can help us avoid such errors of generalization.

In training process, the initial structure of the network is trained, and then the architecture of the trained network is optimized for reduction of prediction errors in generalization process.

The most important parameter in our context will be the penalty parameter C, which affects the training errors and generalization somewhat directly.

In this section, a bound on the generalization error based on the LOO Error is derived.

Procedures that estimate the generalization error of a signature are called "error estimators".