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On the basis of instrument error prediction methods, use modular least squares support vector machines to predict the error of inventory reconciliation and eliminate it subsequently.
Given a training dataset of continuous binding affinities and the similarities among drugs and among targets, SimBoost constructs features for drugs, targets, and drug target pairs, and uses gradient boosting machines to predict the binding affinity for a drug target pair and to generate a prediction interval.
Singh and Shikha [10] utilizes gradient boosting machines to predict toxic effects of nanomaterials.
Then the results were adopted as inputs for support vector machines to predict friction force and friction torque.
It is concluded that the spatial variability in tillage forces has significant effect on the life time of tillage machines and should be considered in the design analysis of tillage machines to predict the life time.
Brunak et al. applied modern machine learning techniques such as artificial neural networks or support vector machines to predict protein annotations based on various features derived from annotated amino acid sequences [19], [20].
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Oak Ridge, part of the Department of Energy, will use the machine to predict the impact of greenhouse gases on crop yields, water supplies, and ocean levels.
In this paper, we propose a novel method by combining wavelet denoising with support vector machine to predict the subcellular localization of proteins for the first time.
In this study, we proposed a novel feature selection algorithm of combined random forest and support vector machine to predict active siRNAs.
In the second part, after gaining the high-level video representations, we use multi-kernel learning-based support vector machine to predict action class [37], where four linear kernels are used, and each corresponds to one type of representations [38].
The two datasets were then used to train a Support Vector Machine to predict poly-cistronic operons in the 284 species of bacteria.
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