Sentence examples for by using support vector from inspiring English sources

EOSC was evaluated and compared with principal component orthogonal signal correction (PC-OSC) by using support vector machine (SVM) classifiers.

In this study we attempt to utilize the electric field data into ionospheric predictions by using support vector machine (SVM), a promising algorithm for small-sample nonlinear regressions.

In this study, the design of experiment (DOE) optimization procedure proposed originally by Chen et al. (1998) and extended later by Chu et al. (2003) has been revised by using support vector regression (SVR) to build models for target processes.

When frames do not get matched to any of existing clusters and certain criteria are met, a new cluster is created in real time and in an on-the-fly manner by using support vector domain descriptors.

We test imagery chain standardization by using support vector machine classifier to classify the land cover of the states of Louisiana and Arkansas, USA, into agriculture, barren lands, forest, urban, water, and wetlands.

A prediction mechanism is realized by using support vector regressions (SVRs) to estimate the number of resource utilization according to the SLA of each process, and the resources are redistributed based on the current status of all virtual machines installed in physical machines.

Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine- SVM-) ba

We employed I-Mutant 3.0 built by unsupervised classification using support vector machine and trained on the most comprehensive dataset derived from ProTherm [ 42] for the prediction of protein stability change for nsSNPs.

This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm.

Fresh stage properties of SCC mixtures with different dosages of water, superplasticizer and coarse aggregate were measured and modeled by Sonebi et al. (2016) using support vector machine approach.

Consistent with this observation, the 44 reporter genes could not produce a CFS classifier using support vector machines by training on a subset of the training set and assessing the predictive power on a separate subset (data not shown).