Feature selection tended to favor necessary improvements over desirable improvements.

他们的选择必须的特性,而不是可拥有的特性.

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Feature selection from the keyboard or'teach and learn'from the hand - box .

通过键盘或手动操作盘上的 ‘ teachandlearn ’键来选择测量元素.

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And a no - search combined feature selection method based on KNN is proposed.

在此基础上,该文提出了一种基于KNN算法的组合式非搜索特征选择算法.

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Feature selection is the key part in image matching based on features.

提出了基于岩石颗粒特征的图象配准算法.

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PRN combined feature selection algorithm is proposed.

并提出改进的PRN组合 特征选择算法.

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This thesis designs 4 main algorithms on the base of Feature Selection algorithm Framework.

在特征选择算法框架的基础上,论文先后设计了4种主要的特征选择方法.

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