... 梯度提升回归树(GBRT) 特征选择算法(Feature selection algorithms) 算法精度评估(Algorithm accuracy evaluation) ...
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So, it is necessary to study feature selection algorithms.
所以，对特征选择算法的研究是十分必要的。
The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.
作者从基于分辨矩阵的粗糙集属性约简中受到启发，提出了一系列基于粗集理论的文本特征选择算法，即DB1、DB2、LDB。
Although there exist numerous feature selection algorithms, new challenging research issues arise for feature selection: from handling a large dimensionality huge number of samples.
尽管出现了大量的特征选择算法，特征选择仍然面临着新的挑战：如何处理高维海量的样本。
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