Sentence examples for boost the classification from inspiring English sources

Huang et al. (2016b) introduced a beta-transformed Bayesian updating model to boost the classification accuracy of category random field.

The probabilities of neighboring syllables are integrated with acoustic features to recursively boost the classification performance of the acoustic models.

However, the majority-voting-based ensemble learning algorithm was performed to boost the classification results of the pairwise bilinear features in the first-stage ensemble learning.

Huang et al. (2016a) stated "Huang et al. (2016c) introduced a beta-transformed Bayesian updating model to boost the classification accuracy of category random field".

However, the majority-voting-based ensemble learning algorithm was performed to boost the classification results of the 5-column features in the first-stage ensemble learning.

Furthermore, a hierarchical clustering method followed by a random forest classification method is proposed to boost the classification performance among confusing classes.

Firstly, MEKLPC gets the side-information and boosts the classification performance significantly in each feature space.

It is caused by the fact that additional information provided by magnitude component remained discriminative as long as it is not considerably modified by the noise disturbance and thus boosted the classification accuracy.

These results support our premise that exploring a plurality of side views can boost the performance of graph classification, and the gSide evaluation criterion in gMSV can find more informative subgraph patterns for graph classification than subgraphs based on frequency or other discrimination scores.

Given W i j = ∑ m = 1 M α m W i j m and the available functional association networks { W m } m = 1 M, the accuracy of protein function prediction is determined by α = [ α1, α2,⋯, α M ]. [ 24] and [ 35] have shown that the target aligned kernel (network) can boost the performance of kernel-based classification and regression.

As reliability of mobile object attributes increases in time (becomes stable), the parallelepiped classification process can also be guided to boost the search of most likely parallelepiped configurations.