Sentence examples for benchmark datasets in from inspiring English sources

For the performance test, five benchmark datasets in FIMDR [15] were chosen.

Its efficiency was verified and compared to several post-processing algorithms on a lot of benchmark datasets in the domain.

Two benchmark datasets in cognitive science were used in our study: (1) StarPlus dataset [24] and (2) Haxby dataset [4].

We chose benchmark datasets in FIMDR [13] including Pumsb, Connect, Mushroom, Chess, and T40I10D100K to test the algorithms in performance.

In addition, we also conduct performance evaluation for the methods with famous benchmark datasets in order to determine their detailed characteristics.

In addition, we also conducted extensive performance evaluation with respect to well-known benchmark datasets in order to analyze detailed features of recent incremental high utility pattern mining approach.

Filter feature selection methods present different ranking algorithms; therefore, we propose an EMFFS method that combines the output of IG, gain ratio, chi-squared and ReliefF to find common features in the one-third split of the ranked features using NSL-KDD benchmark dataset in the Weka.

In order to test the success of our correction for the four different redundant subsets we split this second benchmark dataset in two subsets.

This is because the more stringent of a benchmark dataset in excluding homologous and high similarity sequences, the more difficult for a predictor to achieve a high overall success rate [40].

This is because the more stringent of a benchmark dataset in excluding homologous sequences, or the more subcellular locations it covers, the more difficult for a predictor to yield a high overall success rate.

This is illustrated by the BRCA variants benchmark dataset in Figure 1B and Table 1.