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。
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。
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