搜索资源列表
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 Cancer
基于matlab开发的特征选择算法
- 基于matlab开发的特征选择算法，提取ECG（心电信号）的最有特征组合，降低特征维度。-Based matlab developed feature selection algorithm the extracted ECG (ECG) is the most feature combination to reduce the feature dimension.
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.)
FCBF
- FCBF算法是基于显著的思想，采用后向顺序搜索策略快速有效地寻找最优特征子集的特征选择方法，它采用对称不确定性作为相关程度度量标准，每次选择一个显著特征并删除它的所有冗余特征。(The FCBF algorithm is based on the significant idea, using the backward sequential search strategy to find the feature selection method quickly and effectively.
feature-selection-mRMR-master
- 特征选择方法，用于降低数据维数，常见的一种特征筛选手段，可以从大量变量中筛选特征变量实现保留变量与目标之间的最大相关性(feature selection method for mRMR)
基于粒子群优化算法的特征选择SVM分类
- 针对“BreastCancer”数据集，作为对比，第一次对特征集直接进行SVM分类，第二次使用粒子群算法进行特征选择后再进行SVM分类。并且对比和分析了两次分类的结果。(For "BreastCancer" data set, as a comparison, the first time the feature set is directly classified by SVM, and the second time the feature set is selected
SVMRFE
- 特征选择算法，防止分类结果出现过拟合，提前对多维的特征向量进行选择筛选(A feature selection algorithm)
Relieff特征选择算法
- Relieff特征选择算法，用于特征降维，选择权重比高的的特征。