Sentence examples for more accurate classifications from inspiring English sources
Mitchell et al. also found that the use of PDAs lead to more accurate classifications compared to routine practice [ 21].
For hierarchical clustering, filter FSS always generated more accurate classifications than using all available variables, or after applying some traditional dimensionality reduction technique such as PCA.
The ability to identify subgroups of those at 'extreme' risk or lower risk for CD will enable more accurate classifications of research subjects in clinical trials.
Molecular markers have a great impact on elucidating the biological variance within tumors, they allow new and more accurate classifications and they have the potential to improve diagnosis, estimation of prognosis and treatment decisions in individual patients [ 3- 6].
However, since the strength of this approach is limited by the small sample size and the limited number of gene markers, more accurate classifications of de novo versus recurrence can be achieved by incorporating prior knowledge, hence the Bayesian approach.
Both approaches provide more accurate classifications than those based on BLAST, but they work for fewer sequences, as Pfam hits are less frequent than BLAST hits (typically ∼20% of the genes).
We need to ignore such data for more accurate classification.
Finally, Asm command sequences also produce a more accurate classification result as well which is shown in Section 7.3.
The ensemble framework is applied to sentiment classification tasks, with the aim of efficiently integrating different feature sets and classification algorithms to synthesize a more accurate classification procedure.
Considering the unique temporal and spatial distribution characteristics, the DITI-based model combined with the fuzzy cluster analysis method provided more accurate classification of the rainfall distribution zones.
Feature selection methods have been applied in classification problems to select a reduced feature subset from the original set to achieve a faster and more accurate classification.
