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Abstract
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Article Information:
The Research on Volleyball Trajectory Simulation Based on Cost-Sensitive Support Vector Machine
Yan Binghong
Corresponding Author: Yan Binghong
Submitted: October 31, 2012
Accepted: January 03, 2013
Published: July 25, 2013 |
Abstract:
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Aim of study of the study is to effectively solve the imbalanced data sets classification problem, the field of machine learning proposed many effective algorithms. On Seabrookâs view, now the classification methods for class imbalance problem can be broadly divided into two categories, one class is to create new methods or improve the existing methods based on the characteristics of class imbalance. Another is to reduce class imbalance effect re-use of existing methods by resembling technique. But there are also some drawbacks in resembling method. Sample set sampling may lead to excessive learning; the next sample may result in the training set. Therefore, by dividing the training set, it does not increase the number of training samples; also it is without loss of useful information in the sample to obtain a certain degree of balance in a subset of the problem.
Key words: Artificial Neural Network, autonomous hybrid power system static var compensator, , , , ,
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Cite this Reference:
Yan Binghong, . The Research on Volleyball Trajectory Simulation Based on Cost-Sensitive Support Vector Machine. Research Journal of Applied Sciences, Engineering and Technology, (11): 1950-1955.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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