processing ensemble

In texture synthesis and classification experiments, training a SVM and prediction ( synthesis) require high processing time. To resolve the problem, a new efficient feature selection method based on Bagging ensemble learning method is introduced to reduce the number of characteristics.

最后针对纹理合成及分类实验中训练及预测（合成）速度过慢的问题，提出了一种基于Bagging集成学习的特征选择方法，用来减少特征数量提高执行速度。

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