And it introduces some algorithms of decision tree learning such as ID3, C4.5 and feature subset selection of Inductive learning.
介绍了归纳学习中的决策树学习算法如id3、C4.5和特征子集选择问题。
The feature subset selection is an important problem in machine learning, but the optimal feature subset selection is proves to be a NP hard one.
特征子集选择问题是机器学习的重要问题。而最优特征子集的选择是NP困难问题，因此需要启发式搜索指导求解。
The uncertainty coefficient is an information measure for a feature subset, and it is monotonic, so it can be taken as the feature selection measure.
特征子集的不确定性系数是一种单调的特征子集信息度量，因此可以将它作为特征选择度量。
For the given unclassified model, feature selection requires us to select the most excellent feature subset and it can represent the model which is classified.
对于一个给定的待分类模式，特征选择要求人们从大量的特征中选取一个最优特征子集，以代表被分类的模式。
Then the optimum feature subset is selected from the feature genes with Backward Selection Search Method algorithm and independent tests.
通过“两两冗余”后，依据后向搜索算法选定最优特征子集。
According to the results of data simulation and Diesel engine fault feature selection example, it is proved that this scheme can get optimal feature subset...
数值仿真和柴油机故障特征选择实验结果表明，新方法可以快速、有效地求得优化特征集，是求解特征选择问题的一个较好方案。
According to the results of data simulation and Diesel engine fault feature selection example, it is proved that this scheme can get optimal feature subset...
数值仿真和柴油机故障特征选择实验结果表明，新方法可以快速、有效地求得优化特征集，是求解特征选择问题的一个较好方案。
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