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Text feature is usually expressed as a matrix of huge dimensionality in text mining, and common clustering algorithm are not stable and cannot obtain clustering solution efficiently. Latent Semantic Analysis can reduce dimensionality effectively, and emerges the semantic relations between texts and terms. Clustering ensemble can get better clustering solution than single clustering method. A text...
An ensemble of Elman networks (EEN) is formed by bagging to enhance the performance of the individual networks. The combined density functional theory (DFT) with EEN correction approach has been applied to evaluate the electronic excitation energies of organic molecules. The EEN approach improved DFT calculation results and reduced the RMS deviations from 0.48 to 0.23 eV for the training set. For...
Least squares support vector machines (LSSVM) has been carried out in order to obtain a statistically meaningful analysis of the extended set of molecules. The combined HF with LSSVM correction approach (LSSVM/HF) has been applied to evaluate the transition energies of organic molecules. After LSSVM correction, the RMS deviations of the calculated transition energies reduce from 0.91 to 0.26 eV for...
The neural network ensemble approach (NNE) is proposed for improving the generalization ability of neural networks and to reduce the calculation errors of density functional theory (DFT). The simple averaging approach (NNEA) and weighted averaging approach (NNEW) for combining the predictions of component neural networks we adopted respectively. As a demonstration, this combined DFT and NNE correction...
Least squares support vector machines (LS-SVM) was introduced to improve the calculation accuracy of low level density functional theory. As a demonstration, this combined low level quantum mechanical calculation with LS-SVM correction approach has been applied to evaluate the absorption energies of 160 organic molecules. After LS-SVM correction, the RMS deviations of the calculated absorption energies...
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