Intrusion detection is a classification issue, performance of classification model is determined by feature selection.
入侵检测问题实际上是一个分类问题，特征选择的好坏直接决定了分类模型的性能。
PRN combined feature selection algorithm is proposed.
并提出改进的PRN组合特征选择算法。
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。
Feature reduction can generally fall into feature extraction or feature selection.
特征约简可通过特征提取或特征选择实现。
Data pre-processing, data reduction, feature selection, and feature transformation.
数据预处理，数据压缩，特征选择与特征变换。
This paper presents a novel feature selection method which is based on class feature domains.
本文介绍了一种基于类别特征域的特征选择方法。
A new feature selection algorithm based on Immune Clonal selection algorithm (ICSA) is proposed.
提出了一种基于免疫克隆选择算法的特征选择方法。
Several feature selection methods were analyzed. An improved mutual information algorithm was proposed.
分析了常用的几种特征选取方法，提出了改进互信息算法。
In this paper, we propose a novel feature selection method based on concept extraction and shielded level.
本文提出了一种新的基于概念抽取和屏蔽层的特征选择方法。
Cross validation, feature selection, quasi-random numbers, and partial least squares in Statistics Toolbox.
在统计工具箱中，增加了交叉验证，特征选择，拟随机数和偏最小二乘法。
In this paper, a posterior-probability-based feature selection algorithm is proposed for imbalanced datasets.
针对不平衡数据集，提出一种基于后验概率的特征选择算法。
This paper employs feature selection theory and pattern aggregation theory to reduce feature space dimension.
应用特征选取和模式聚合理论以降低特征空间维数。
This paper presents a method of neural networks feature selection based on data attributes importance ranking.
提出一种基于数据属性重要性排序的神经网络属性选择方法。
The research emphasizes on the feature selection in internal-nodes, and designs a new Distance Difference Function.
论文重点研究了决策树内部结点的特征选择方法，设计了一个新的距离差函数。
In particular methods for confidence estimation and feature selection with Support Vector Machines will be described.
特别是支持向量机的特征选取和信赖度估计方法。
Two important research directions of text classification are: feature selection method and text classification algorithm.
文本分类的两个重要的研究方向是：特征选择与文本分类算法。
In this paper, we introduce an algorithm which is using the importance of attribute with heuristics for feature selection.
本文提出一种基于属性重要度的启发式特征选取算法。
However, the result of the feature selection in unsupervised learning is not as satisfactory as that in supervised learning.
但是，无指导学习环境下的属性选择往往无法取得像有指导学习环境下那样令人满意的结果。
This paper presents two algorithms of linear feature selection used for the study of strong earthquake zoning in Beijing area.
本文介绍两种线性特征选择算法，并用于北京地区强震危险区划的研究。
The techniques of feature extraction, feature selection and design of classifier for passive sonar target recognition are reviewed.
文章对被动声纳目标识别的特征提取、特征选择和分类器设计方面进行了回顾。
Text feature selection is a process of recognizing and deleting redundant information and enhancing training documents cluster quality.
文本特征选择是最大程度地识别和去除冗余信息，提高训练数据集质量的过程。
The selection of the evaluating index system is the key to enterprise credit assessment, which is essentially a feature selection problem.
评估指标体系的选取是企业信用评估的首要问题，它是一个特征选择问题。
This thesis improves classification using gene expression data method in two aspects: feature selection and SVMs classification algorithm.
针对基于基因表达数据的分类，本文从特征基因选择和支持向量机分类算法两个方面进行了改进。
By designing the BP-type ANN based CCT estimators with the selected features as inputs, the effectiveness of feature selection is further verified.
通过构造基于BP网络的临界切除时间(CCT)预测器进一步验证了特征提取的有效性。
With regard to the problem that original feature in image classification is mass and redundancy, a new image feature selection method was presented.
针对目前图像识别中原始特征数量大、不相关特征多以及冗余等现象，提出了一种图像特征选择方法。
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 improving the performance of multiple classifier system, a novel method of ensemble feature selection is proposed based on generalized rough set.
为改善多分类器系统的分类性能，提出了基于广义粗集的集成特征选择方法。
For improving the performance of multiple classifier system, a novel method of ensemble feature selection is proposed based on generalized rough set.
为改善多分类器系统的分类性能，提出了基于广义粗集的集成特征选择方法。
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