Sentence examples for a higher classification of from inspiring English sources

However, confidence scores for individual binding sites can be assessed by a standardized statistical analysis to allow a higher classification of strength of evidence for a subset of the data.

Graduate entry programmes encourage applicants who hold a higher classification of degree, and match a set of criteria determined by the institution, to study to become a healthcare professional.

Extensive experimental results demonstrate that the GESR-LR method can obtain a higher classification accuracy than other state-of-the-art methods.

Under the usual system, students whose average marks are narrowly short of a higher classification (the threshold for a first is 70%) could be graded up only if they had sufficient individual marks of a first-class standard, said the report in the THES.

Films are usually given a higher classification if they include footage of someone going to town between a woman's legs and female ejaculation in porn is literally banned under BBFC laws in the UK.

The evaluation of our algorithm, called integrated prognosis risk estimation (IPRE), and the experimental comparisons with other prognosis based classifiers demonstrated that the IPRE algorithm outperforms other classifiers by achieving a high classification accuracy of 82% (with specificity of 88% and 877% (with specificity of 95%) in the Desmedt [ 22] and the Vijver [ 3] datasets, respectively.

However, a recent reassessment of the higher classification of eukaryotes, based on ultrastructural and molecular approaches, recognized six supergroups, which can be tentatively referred to as kingdoms [84], and the marine phytoplankton species have representatives in four of these supergroups [85].

Beginning with a comprehensive character analysis pertaining to morphology, physiology, and behavior related to adults, larvae, and eggs, the useful taxonomic keys (adults and puparia) are presented for the genera of different geographic regions, followed by a comprehensive treatment of the higher classification of marsh flies (pp. 199 396).

Through the comparison of the results of the SVM and BP classification models, the SME credit risk assessment based on SVM from the perspective of SCF results in a high classification accuracy of 93.65 %, which is significantly higher than the classification accuracy of 55.56 % of the BP neural network.

Canonical analysis of principal components (CAP) of all roving herbivorous fish yielded a high classification success of 93.1% across all habitat types (i.e. only 6.9% misclassification error).

The QUWI database which includes writer demographics information has been employed for gender classification in a number of recent studies and a highest classification rate of 69.25 % is realized [150].