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As mentioned above, there are two parameters σ and C in Adaptive Boosting based on RBFSVM (AdaBoostRBFSVM) and one parameter C in Adaptive Boosting based on linear kernel (AdaBoostLSVM) which have to be set beforehand.
Adaptive Boosting based on linear kernel.
In this paper, we try our best to find solutions to the following problems: Can we use the component classifiers based on linear kernel or RBF kernel to get better generalization performance in AdaBoostSVM?
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Second, a backward feature selection approach based on linear-kernel SVM was used to selected drug response-relevant features instead of a screening scheme by CCLE and CGP.
For DPC feature based model, the training classifiers based on linear and polynomial kernels yielded accuracies of 83.74% and 81.43% respectively.
We have developed a novel fault diagnosis approach of analog circuits based on linear ridgelet network using wavelet-based fractal analysis, kernel principal components analysis (kernel PCA) as preprocessors.
A novel formulation of combustion balance is presented, based on linear operators, which isolates the wastefeed vector from the invariant combustion stoichiometry kernel.
Figure 9 shows a classification example of SVM based on the linear kernel and the RBF kernel.
Intuitive leaders do not take action based on linear thinking.
The four clustering methods are (1) the k-means clustering of multidimensional scaled RMSD values based on a linear kernel without suppling k explicitly, (2) the hierarchical clustering algorithm with dynamic tree cut based on a linear kernel without using an explicit threshold, (3) PCA (principal component analysis) with a linear kernel and (4) PCA with an RBF (radial basis function) kernel.
A local scoring algorithm based on local linear kernel smoothers was implemented to estimate the proposed logistic GAM.
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