feature subset selection的例句大全

Based on rough sets, a new heuristic algorithm is presented to solve the difficulty. Research on the Feature Subset Selection of Complex Decision Tables

基于粗集理论，本文提出了一种新的决策表最优特征子集选择的启发式算法.复杂决策表的特征提取方法研究

OFFSS ( Optimal Fuzzy-Valued Feature Subset Selection) is an optimal feature subset selection based on fuzzy-valued extension matrix.

最优模糊特征子集选取OFFSS（Optimal Fuzzy-Valued Feature Subset Selection）是一种用模糊扩张矩阵进行最优特征子集选择的方法。

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。

After analyzing problems of the feature subset selection in the field of data mining, a new algorithm of feature subset selection based on the improved genetic algorithm is proposed.

对数据挖掘中的特征子集选择问题进行分析，提出了基于改进遗传算法的特征子集选择算法。

As optimal feature subset selection ( OFSS) is an NP-hard Problem, it is of realistic significance to find an approximative algorithm.

指出最优特征子集选择问题（OFSS）是个NP-Hard问题，寻找一个近似算法具有现实意义。

The approaches to the subject include: genetic algorithm for optimal feature subset selection; k-fold cross-validation method for error rate evaluation and BP neural network for fault classification.

针对此问题，提出使用基于绕封模型的故障特征选择方法，它采用遗传算法对特征集寻优，样本划分法进行错误率预测估计和BP神经网络学习算法进行分类。

Optimal fuzzy-valued feature subset selection ( OFFSS) method has been efficient for feature subset selection of two-class problem, which can be classified into positive and negative classes.

最优模糊值特征子集选取OFFSS（Optimal Fuzzy-Valued Feature Subset Selection）适用于数据库中示例只分为正反两类的特征子集选取问题，而不适用于多类的特征子集选取问题。

OFFSS ( Optimal Fuzzy-valued Feature Subset Selection) is a new fuzzy-valued feature selection method that selects an optimal feature subset from the feature space by considering both the overall overlapping degree between two classes of examples.

OFFSS（Optimal Fuzzy-Valued Feature Subset Selection）是一种新的模糊值特征选取的方法，是基于两类事例集合的重叠程度来选取特征空间中最优特征子集。

Optimal fuzzy-valued feature subset selection ( OFFSS) method is proposed to deal with the problem of the expression of the imprecise data. OFFSS use the fuzzy set to express the imprecise data substitute the traditional discrete method.

随着基于模糊值最优特征子集选取OFFSS的提出，对于实际应用中语义含义不精确数据（如：大，中，小）的表示，OFFSS方法采用模糊集合的方式代替了传统离散值的方式。

The target function adopted in this method is more suitable for SVR. Moreover, by considering that redundant feature is small in special experiment data, this work uses sequential backward selection method in the fea-ture subset selection.

该算法采用了一个适合支持向量回归（SVR）的新目标函数，并在特征子集选择中根据实验数据集冗余特征较少的特点，采用顺序后向选择算法。