In the feature selection stage, the computing approximate gains in parallel is adopted in order to solve the computational expensiveness of the model and system spending.
在特征选择阶段，采用计算近似增益的平行算法，解决模型计算量过大和系统开销问题。
This paper researches into the characteristic of aggregate query rewriting and gives a kind of rapidly approximate query computing model based on aggregate query rewriting under the data warehouse.
研究了聚集查询重写的特征，根据数据仓库环境下聚集查询需要快速计算结果的特点，给出了一个基于聚集查询重写的快速近似计算模型。
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