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Aggregating Density Estimators: An Empirical Study
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作者 Mathias Bourel Badih Ghattas 《Open Journal of Statistics》 2013年第5期344-355,共12页
Density estimation methods based on aggregating several estimators are described and compared over several simulation models. We show that aggregation gives rise in general to better estimators than simple methods lik... Density estimation methods based on aggregating several estimators are described and compared over several simulation models. We show that aggregation gives rise in general to better estimators than simple methods like histograms or kernel density estimators. We suggest three new simple algorithms which aggregate histograms and compare very well to all the existing methods. 展开更多
关键词 Machine Learning HISTOGRAM Kernel Density ESTIMATOR BAGGING BOOSTING STACKING
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