Sentence examples for several datasets and from inspiring English sources
This is convenient if we have several datasets and they should all be normalized using the same normalization factors.
The algorithm's high specificity and sensitivity were demonstrated by testing several datasets and, at the best combinations, they both reached 95%.
The evaluation was performed over several base classifiers, several datasets and several query selection criteria, including d-Confidence and its baseline criteria.
Our system was evaluated with several datasets and results have shown that performance is very close to the state of art techniques in the source code identification field.
This article details the developments and improvements that have been made to MetFrag since the original publication, including a detailed evaluation on several datasets and specific examples to demonstrate the use of MetFrag2.2 in small molecule identification.
Image clustering experiments are conducted to demonstrate the effectiveness of the proposed methods on several datasets and compared with some related works based on NMF together with k-means clustering method and PCA as baseline.
b Violin plots showing the distribution of SAscore values across several datasets: decoy and active DUD-E compounds, FDA approved drugs, molecules generated by eSynth for the DUD-E targets, and natural products (NP) from the NuBBE and UNPD databases.
This implies that the DisGeNET RDF resources are linked out to other external resources in the Linking Open Data Cloud such as UniProt and several datasets from the Bio2RDF (48) and Linked Life Data (49) subnetworks, spanning the information on genotype-phenotype associations in the Semantic Web and promoting DisGeNET discoverability.
In order to achieve efficient structure learning, we have utilized a Gibbs sampling to search for global optimum and applied GBNet successfully to several datasets in yeast and human [ 5].
Interestingly we have used several datasets, both kinetic and non kinetic experiments from yeast and human.
Experimental results on several datasets of CT and MRI images show that the proposed algorithm outperforms other compared methods in terms of both subjective and objective assessment.
