Sentence examples for Large-scale classification from inspiring English sources

Large-scale classification, or as Cavalier-Smith puts it [56], mega-classification, of prokaryotes, deals with higher taxonomic ranks such as phylum, class, and order (at present, ranks higher than order are not covered by the International Bacterial Code [57]).

Both our model itself and the solving algorithm can guarantee that it can deal with large-scale classification problems with a huge number of instances as well as features.

However, this has not yet been quantified for large-scale classification of many cover types with subtle differences in complex, noisy hyperspectral patterns.

In their study on multistage adaptive testing for a large-scale classification test (design heuristic assembly, and comparison with other testing modes), Zheng et al. (2012) designed an MSCAT for a large-scale classification test and performed the automated test assembly using a heuristic method.

This high speed makes the proposed method well applicable to perform large-scale classification of microorganisms.

Simultaneously, they can also be carried out with other libraries, such as LIBLINER [ 29], which is alternative for SVM classification, especially appropriate for large-scale classification problems.

Yinan Yu, K. Diamantaras, T. McKelvey, S. Y. Kung, "CLAss-specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification", the IEEE Transactions on Neural Networks and Learning Systems (TNNLS-2016-P-6571), in press.

Data compression techniques had been used for applying the models on large data, that is, for large scale classification, dictionary learning while for large scale regression pre-clustering approach had been applied.

In this post genomic era, when the amount of genome sequence data increases so rapidly, the high efficiency and novelty of the proposed method make it feasible for large scale classifications of microorganisms and phylogenetic studies of species with similar metabolic properties or incomplete genome sequences.

Recently, transfer learning techniques have been applied successfully in many real-world data processing applications, such as cross-domain text classification, constructing informative priors, and large-scale document classification [55 57].   5.

Our experiments show very good results and confirm that the balanced training algorithm and parallel solutions are very essential for large-scale visual classification in terms of training time and classification accuracy.