Sentence examples for gained classification from inspiring English sources

Depending on the gained classification, analyzing algorithms can be performed again with an adapted level of detail.

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.

It can be observed from Table 2 that the stress level classification can be achieved by features from frequency domain and gained outstanding classification accuracy.

Knowledge gained through classification of microarray gene expression data is increasingly important as they are useful for phenotype classification of diseases.

The atomic theory of matter, a transcendental scientific breakthrough, was based in large part on insights gained from classification.

Of course, if drivers gained employment classification Uber would also have to follow minimum wage laws and other costly regulations that regular employers are required to follow. .

Given the multiple alignment, LocARNAscan gains classification strength, but does not match the excellent performance of Infernal with sequence information.

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.

Here, the information of chemical-chemical interactions and protein-protein interactions were retrieved from Search Tool for Interactions of Chemicals (STITCH) [ 12] and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) [ 13], respectively, as the resources of gaining the classification features.