Sentence examples for the class of sampling from inspiring English sources

For the class of sampling designs including srswor, the same estimator remains optimal within the class of all quadratic design unbiased estimators for a particular case of the assumed random permutation model.

The species of charge is related to the class of sample.

SU lists the ranked 256 features with the maximum relevance to the class of samples.

When this model is fully developed, it is used to predict the class of sample 1.

After running the mRMR software, we obtained two tables for each of the ten datasets (see Supplementary S2): one is called MaxRel feature table that ranks the features according to their relevance to the class of samples and the other is called mRMR feature table that lists the ranked features by the maximum relevance and minimum redundancy to the class of samples.

One is called MaxRel feature table that ranks the features based on their relevance to the class of samples and the other is called mRMR feature table that lists the ranked features by the maximum relevance and minimum redundancy to the class of samples.

In this study, using the statistics toolbox of Matlab (The MathWorks, R2008a), the analysis of mRMR ranked the metabolites according to their relevance to the class of samples concerned, and also takes the redundancy of metabolites into account.

Supplemental Materials S1 (in Supplementary Material available online at http://dx.doi.org/10.1155/2014/905951) are two results using the mRMR software: one table is a maximum relevance feature result that ranks the 126 features based on their relevance to the class of samples; the other is called the mRMR feature table that lists the 126 ranked features according to mRMR criteria.

By running the mRMR software, we obtained two ranked feature lists (see Supporting Information Text S2): (1) the MaxRel feature list that contained all the 646 features ordered by their relevance to the class of samples, (2) the mRMR feature list that contained all the 646 features ordered by the maximum relevance and minimum redundancy criteria.

In the Leave-one-out cross-validation KNNxVal models, 43 models were generated using 42 samples to predict the class of the sample that was left out.

In most of the known cases in sampling theory the classes of the sampled functions are integral transforms defined on a (L^{2} -space.