Wei (ed.)'s Applied Engineering Sciences PDF

By Wei (ed.)

ISBN-10: 0813908671

ISBN-13: 9780813908670

ISBN-10: 1138026492

ISBN-13: 9781138026490

ISBN-10: 1315762242

ISBN-13: 9781315762241

This complaints quantity comprises chosen papers awarded on the 2014 AASRI overseas convention on utilized Engineering Sciences, held in Hollywood, los angeles, united states. Contributions disguise the newest advancements and advances within the box of utilized Engineering Sciences.

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First, a new training data set can be generated by an under-sampling and SMOTE oversampling hybrid method from the original examples. Then, every based classifier was trained on a new data set, while the regularized negative correlation penalty terms were included in the cost function of NNE, in order to overcome over-fitting and promote the ensembles’ generalization ability. Our contributions are to propose hybrid pre-sampling and neural network ensembles with an RNCL algorithm for imbalanced data classification.

Data sets Examples Features Imb. ratio Application Abalone_7 Balance Yeast_ME3 Ionosphere Car Flare 4175 625 1480 750 1725 1065 Table 2. 067 Main parameters of the based classifier. 001 20 20 20 20 20 20 1000 500 1000 500 500 1000 of “false positive” instances, and the F-measure is defined as: According to five-fold cross validation [16], all examples are randomly divided into five sets. The classifier is trained five times, each time with different sets held out as validation sets and other sets held for training.

2956–2968. Dolecek, G. J. & Mitra, S. K. 2005. A new two-stage sharpened comb decimator. IEEE Transactions on Circuits and Systems: I 54(4): pp. 994–1005. X. R. China L. R. Q. He National Computer Network and Information Security Management Center, Beijing, China ABSTRACT: Personalized recommendation has been widely used in the field of e-commerce sites, yet the cold start problem is still not solved and much more attention is paid to a single e-commerce site. In this paper, starting from multiple e-commerce sites, we propose a recommendation algorithm to effectively and efficiently relieve this problem.

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Applied Engineering Sciences by Wei (ed.)


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