Sentence examples for evaluated data set from inspiring English sources
The fuzzy k-means fuzziness factor determines the degree of overlap between the generated clusters and analysis of the evaluated data set found that a value of 1.05 generated well-defined and differentiated clusters.
While E. coli total tRNAs were used to develop this exclusion list strategy and L. lactis total tRNAs served as a previously evaluated data set to confirm the general characteristics of this approach, a more fruitful application would be for RNA modification mapping of bacteria that are presently uncharacterized.
The distribution of each of these characteristics in the EREG evaluated data set was also similar to that observed in the total study population.
The workflow, given a target or problem, automatically accesses and processes molecular data, calculates descriptors and fingerprints, evaluates data set modelability, selects optimized set of features by using an established methodology [45] and follows an unbiased standard protocol [22, 44] of QSAR model building by external and internal validation.
Across all evaluated data sets, we find that incorporation backbone sampling improves accuracy substantially, irrespective of using a crystal or NMR structure as the starting conformation.
On the evaluated data sets, IFR demonstrates that at least 20 iterations are required before we see a significant loss in discriminatory power, providing hundreds of genes for further analysis.
The characteristics and a short description of the medical meaning of the evaluated data-sets are summarized in Table 1.
The results are displayed as the mean, minimum and maximum number of different trees constructed on the 8 evaluated data-sets and are within an accuracy class.
Number of diverse trees with an improvement in relative accuracy of [ min%, max%] compared to the CART tree, displayed as mean(min, max) referring to the mean, minimum and maximum number of trees constructed on the 8 evaluated data-sets.
Furthermore, the cell cycle cluster of genes (PC1 for each data set) was as effective as all of the other established classifiers we examined when used to evaluate data sets other than those from which they were derived (Table 2) [see Additional file 2].
