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Relevance vector machine (RVM) is a state-of-the-art technique for regression and classification, as a sparse Bayesian extension version of the support vector machine. The kernel function and parameter selection is a key problem in the research of RVM. The real-world application and recent researches have emphasized the requirement to multiple kernel learning. This paper proposes a novel regression...
Combined the modified AdaBoost.RT with extreme learning machine (ELM), a new hybrid artificial intelligent technique called ensemble ELM is developed for regression problem in this study. First, a new ELM algorithm is selected as ensemble predictor due to its rapid speed and good performance. Second, a modified AdaBoost.RT is proposed to overcome the limitation of original AdaBoost.RT by self-adaptively...
Generalization performance of support vector machines (SVM) is affected by parameter selection. How to select optimal parameters to achieve the best training model has been a hot research spot. In order to improve generalization performance of SVM, K-fold cross validation is used to select parameters for training. However, K-fold cross validation is time-consuming, especially for large number of samples,...
Bankruptcy prediction has been one of the most challenging tasks and a major research topic in accounting and finance. In this paper, bagging ensemble, a popular technique in the machine learning community, is proposed to improve the prediction performance of artificial neural networks in bankruptcy prediction analysis. The experiments conducted on the public dataset show that the proposed approach...
The Montgomery county corrections program is a program designed to address the problem of overcrowded jails by providing an out-of-jail rehabilitative program as an alternative. The candidate offenders chosen for this program are offenders convicted on nonviolent charges and are currently chosen subjectively with little statistical basis. In addition, historical data has been recorded on offenders...
An approach of a mean hourly wind speed conformal prediction in wind farm is proposed. Conformal prediction is a new prediction methodology. It can be used not just to make predictions but also to estimate the confidence under the usual independent and identically distributed assumption. Based on support vector regression, wind speed regions are predicted by inductive confidence machine. Wind speed...
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