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Many statistic based machine learning methods depend on the estimation of probability density function from observations. Non-parametric density estimation algorithms based on minimizing expirical risk using support vector machine (SVM) are quite general and powerful, but have a significant disadvantage in the smoothness of estimation result. In this paper, we studies the vicinal risk minimization based estimation algorithm, and propose a new construction algorithm of vicinity function. Experiments are carried out which prove that the performance of new algorithm is obviously improved.
Information and Computing (ICIC), 2010 Third International Conference on (Volume:4 )
Date of Conference: 4-6 June 2010