假设空间中存在一个向量场和一个曲面。
s Let's say that we have a vector field and s, a surface in space.
如同台式机，假设空间不是问题，你应该更喜欢double。
As with desktop machines, assuming space isn't an issue, you should prefer double to float.
通过扩展特征向量，元学习增强了对假设空间的表达能力，降低了系统的偏差。
The classification results of basis classifiers were added to original feature vector to obtain the meta-level data, which enhanced the search ability in hypothesis space and decreased system bias.
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