Sentence examples for classifications to classifications from inspiring English sources

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Whereas molecular biology has permitted for most living organisms a progressive shift from character-based classifications to classifications based on genetic markers [ 5], no satisfying method for classifying phages exists at present.

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When we compared the MST classification to classification by 16S rRNA genotypes, we observed that 16SrRNA type I strains were restricted to clusters 1 and 2 (Houston-1), whereas most type II strains were grouped into clusters 3 (Marseille) and 4.

Finally, we adopted the logistic regression classifier or the Softmax regression classifier to realize the classification in the second category classification or multiple classifications to the target objects in the sky, such as UAV, birds, and kites.

We averaged the SDI values for the top most dominant species in every class within the classifications to determine which classifications tended to produce classes with more dominant species.

Next, probabilistic tract-strength was defined as the average of the two proportions that resulted from the seed-to-classification and classification-to-seed analyses.

The classification algorithms are not limited to classification of the braking states, but they can be used for other motion related maneuvers on the road surfaces.

Table 2 shows the comparison of SVM, IAEMSVM, and the proposed IREMSVM with respect to classification accuracy when the classification is proposed with the 19 selected features obtained from the proposed feature selection algorithms.

Comparisons based on experiments using the LDC corpus revealed that an automatic emotion classification system that modelled contours outperformed one that modelled statistical distributions by 6.1% (relative) with regards to classification accuracy, and the classification accuracy of this contour-based system was comparable with human classification accuracy.

In a demonstration of their technique aimed at web page classification, the addition of unlabeled samples decreased classification error relative to classification using only labeled data.

All together, this information can be visualized on a gene and donor specific way including annotation of significance, classification and proportionate contribution to classification.

Of the 18 patients (15 men and 3 women), there were 5 patients were diagnosed preoperative IIB stages according to classification of the Association Research Circulation Osseuse classification (ARCO) and the remaining 13 patients were in ARCO IIIC stages.

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