搜索资源列表
Relief
- 经典特征选择程序，在特征提取完成后进行特征选择可以达到提取有用成分的目的-Feature selection procedure, after completion of the feature extraction feature selection can achieve the purpose of extracting useful components
pluslr
- 顺序前进法特征选择，顺序后退法特征选择计算正确率-Sequential forward feature selection method, the sequence backward feature selection method to calculate the correct rate
question4
- 特征选择与变换的算法实现,计算贡献率与主成分分析-Feature selection and transformation algorithms to calculate the contribution rate and principal component analysis
Class-separability
- 类可分离性的判别，特征选择与特征提取的任务是求出一组对分类最有效的特征因此需要有定量分析比较的方法，判断所得到的特征维数及所使用特征是否对分类最有利，这种用以定量检验分类性能的准则称为类可分离性判据。 类别可分离性判据，用来检验不同的特征组合对分类性能好坏的影响，并用来导出特征选择与特征提取的方法。 理想准则：某组特征使分类器错误概率最小-Class separability of discrimination, feature
feature_selection
- 特征选择-feature selection。。。。。。。。
audio-qualities
- 1、顺序后退法特征选择算法 2、SFFS 特征选择算法 3、ISD算法 4、LLR算法 5、CZD算法-1, the order backward method of feature selection algorithm 2, SFFS feature selection algorithm 3, ISD algorithm 4, LLR algorithm 5, CZD algorithm
tztq
- 特征选择与提取 特征点 matlab应用 可用-Feature selection and extraction of feature points matlab applications available
5
- 乳腺癌的发病率在女性癌症中占据首位，开展乳腺癌的诊断和防治研究具有重要的科学意义和临床实用价值。 文中主要研究的是对超声图像进行分析，对其灰度和纹理特征提取进行研究，并在特征选择阶段使用类间距对单个特征的分 类能力进行评价，为后续研究计算机辅助诊断系统奠定一个初步基础。 -Extraction of Gray and Texture Features based on Ultrasonic Image of Breast
新建 WinRAR 压缩文件
- 一种新的特征选择和基于分解的多目标进化算法(a new feature selection and weighting method aided with the decomposition based evolutionary multi-objective algorithm called MOEA/D)
模式识别
- 模式识别分类，聚类，特征提取，特征选择，特征变换(Pattern recognition, classification, clustering, feature extraction)
CACC
- 波段选择 特征选择 属性选择 matlab 很不错(Band selection feature selection attribute selection matlab very good)
Relief特征选择
- relief 特征选择算法，用来约简数据属性。图像处理等(Relief feature selection algorithm is used to reduce data attributes. Image processing, etc.)
时频域统计特征
- 信号的时频域统计特征，可用于后续模式识别,特征选择，特征提取。(The time-frequency statistics of the signal can be used for subsequent pattern recognition.)
rfuncs
- 用随机森林的方法进行特征选择，对200了影像特征数据进行分类(Feature selection using random forest methods)
001
- 针对多维特征可以进行特征选择和降维，可以进行后续的模式识别。(Feature selection and dimension reduction can be carried out for multidimensional features, and subsequent pattern recognition can be carried out.)
特征提取程序
- 特征提取，随机森林实现特征重要性排序，用python实现(Feature extraction and classification of characteristic importance in random forest)
基于极限学习G-score
- G-score是一个特征排序的准则，极限学习机结合G-score是一种filter+wrapper的混合特征选择算法(G-score is a criterion of feature sorting. Limit learning machine combined with G-score is a hybrid feature selection algorithm of filter+wrapper)
REC-FSA-master
- 利用信息熵聚类对故障多特征量进行特征选择(Feature selection by using information entropy clustering for multiple features of fault)
feature_selection_peng
- 用于进行特征选择的方法，可以对数据进行降维，减少冗余。(For the method of feature selection, the data can be reduced and redundant.)
FSASL-master
- 该方法通过计算核空间距离从而来对样本进行特征选择。(The method is used to select the features of the samples by calculating the distance of the nuclear space.)