A New Sequential Algorithm for Regression Problems by Using Mixture Distribution
作者： Takafumi Kanamori
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摘要: A newsequen tial method for the regression problems is studied. The suggested motivated by boosting methods in classification problems. Boosting algorithms use weighted data to update estimator. In this paper we construct a sequential estimation from viewpoint of nonparametric using mixture distribution. algorithm uses residuals training data. We compare greedy simple simulation.
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