(1) Feature set selection Through selecting the preferred features, users can observe the implied utility/privacy information.
To test our hypothesis correction, four schemes of core gene set selection were selected.
Firstly, we propose a candidate node set selection mechanism, which selects the forwarders based on the vehicle's geographic location and the link's quality.
The goal of signature gene set selection is to select the genes that are expressed differentially.
Subsequently, a probe set selection algorithm was carried out to select a representative probe set for each gene starting from all genes selected by ANOVA and PCA analysis.
Detailed data in the rule set selection process is described.
Section 4 discussed the BE functions set selection.
Here is how the candidate node set selection mechanism works.
Thus the measurement set selection and the sampling profile can be determined simultaneously.
We will call these functions set selection functions or neighborhood selection functions.
To this end, three objective functions are proposed as optimization criteria for training set selection.
