Sentence examples for gain classification from inspiring English sources
The MICA-based support vector machine applies the classic support vector machine (SVM) [ 16] to the meta-samples calculated from MICA to gain classification in a low-dimensional space.
Depending on the gained classification, analyzing algorithms can be performed again with an adapted level of detail.
Given the multiple alignment, LocARNAscan gains classification strength, but does not match the excellent performance of Infernal with sequence information.
To rank various combinations, the basis of percentage gain in classification accuracy with respect to maximum classification accuracy obtained using EWT feature extraction method with combination of various feature selection methods has been chosen.
They also show the gain from classification tree post-processing of the predictions from lower-level forecasts.
The root gene has the most information gain for classification, and the other nodes genes appear in descending order of power in discrimination [38].
The statistical significance of the coefficient associated with the analyzed gene determined the gain in classification power of the survival model compared with the clinical model alone.
Although they gain a classification score of 97% with gene subsets of size two, they did not find any gene pair with a classification score of 100%, and they did not identify any important genes.
Similar to the MICA-SVM algorithm, the multi-resolution independent component analysis based linear discriminant analysis (MICA-LDA) applies the classic LDA to the meta-samples obtained from MICA to gain sample classification.
The results in Table 2 show that three subsets still gain good classification performance with large feature reduction ratio after feature selection, and they are very close to the performance of original features correspondingly.
We attribute this smaller gain in classification performance to the short protein sequences in Dataset III, which pose a greater challenge to the three alignment-free similarity measures examined in this study.
