Sentence examples for classification better than from inspiring English sources

In particular, the 6mer seeds show a significant increase of specificity leading to a classification better than an average random prediction (MCC > 0, Supplementary Table S6).

The difficulty in classifying this undefined subtype might be because of partial sequencing of the strains identified, although Lu et al. showed that the 5′ end of the ORF2 region matches the complete genomic sequence for HEV classification better than other regions of the HEV genome (5 ).

The present article is therefore aiming to develop principles and methods for the construction of a chemical expert ontology of compound classes that shall allow to represent the high complexity of chemical classifications better than before and that could be used for automated classification of compounds in databases or text documents.

The hybrid classification technique improves the classification accuracy better than using either unsupervised or supervised classification techniques alone (Lillesand and Kiefer 2000).

In summary, in the UPLIFT population of moderate to very severe COPD patients, the 2013 GOLD classification performed better than the old classification when predicting future exacerbations, whereas the old classification system performed equally well or better when predicting mortality and lung function decline.

The fractures were defined as a buckle if it was rated as such by at least 6 of the 8 most experienced doctors on both readings The overall interobserver reliability of this fracture classification is better than most other reported agreement for fracture classification systems in adults.

The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.

For k-means classification, the values are higher 1 to 2% compared to Ward classification, 10% better than McQuitty and Complete linkage and 13% to average linkage.

We do not mean to suggest that this classification is better than any other, but we are suggesting that an empirical approach, independent of a priori classification, can be very useful in light of a gap in understanding the biological effects of simultaneous exposure to multiple congeners in different proportions.

We show classification with better than 99% accuracy for DNA hairpin molecules that differ only in their terminal Watson-Crick basepairs.

For the Gaussian-blurred database, the proposed NR metric based on image classification performed better than the other NR blur metrics.