Sentence examples for datasets indicates that from inspiring English sources

An extensive experimental comparison with two public EEG datasets indicates that the MKELM method gives higher classification accuracy than those of the other competing algorithms.

The selected bands for the AVIRIS datasets differ from those for the LOPEX and PROSPECT-SAILH simulated datasets, and this inconsistence of the selected bands for different datasets indicates that the GA-PLS method has the advantage of tuning the optimum bands for PLS regression and accommodating the effects of confounding factors.

On the other hand, the fact that the two CYP450 external datasets show quite different profiles with KDE, and this same technique has very different outcomes between all three datasets indicates that this method is not reliable as a standalone measure for AD determination and there may be other factors that should be taken into account.

Analysis of the highest-confidence ChIP sites, the 1017 sites that are common to both datasets, indicates that more than 90% of the ERE-like sequences at these loci are not perfect consensus sequences.

MYC over-expression in basal cancer in other datasets can be distinguished on the basis of frequency [50], but our analysis of the five meta-analysis datasets indicates that it is not a prominent feature, ranking below the top 1000 differentially expressed mRNAs.

Discovery of alternative transcripts in our datasets indicates that ~50%% of genes expressed in larvae have alternative transcripts.

Experimental results on two large real datasets indicate that the proposed incremental slope-one recommenders can correctly reflect the increments of dynamic datasets with high computational efficiency.

All observational datasets indicate that the volumetric distribution shifts toward lower salinities, i.e. on average, fresh regions become fresher at a higher rate than saline regions become more saline (see Fig. 2 and supplementary Fig. 1).

The test results of the ISPRS datasets indicate that the proposed algorithm achieved low commission errors ranging from 1.53% to 6.91%.

Extensive experiments on several commonly used image SR testing datasets indicate that the proposed method achieves state-of-the-art image SR results.

Experiments on two real-world datasets indicate that the quality of learned semantic vectors and the performance of social emotion classification can be improved by our models.