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ati
- 邻域粗糙集在轮对踏面缺陷图像特征选择的应用-Neighborhood rough sets in wheel tread defects application image feature selection
FaceDetect_V1.3
- FaceDetect_V1.3.zip 前向特征选择人脸检测-Forward Features Selection Face Detect
e4k-means-althogrim
- 基于K—Means的中文文本聚类算法的研究和实现。中文文本聚类的主要技术，特征选择，共享最近邻的K-Means的改进算法。基于k-Means的实现和实验。-Based on the Chinese version of K-Means clustering algorithm and implementation. The main technology of Chinese Text Clustering, feature selection, shared nearest neighbor
feature.tar
- 多级CGH数据分类和特征选择算法，可以直接运行的一些资料，希望对大家有帮助！-Classification and feature selection algorithms for multi-class CGH data
Texturefeatureselect
- 摘 要: 本文基于Landsat7ETM+全色图像,以浙江省临安市大峡谷镇为研究区,进行基于遗传算法的遥感图像纹理特征选择的研究-Abstract: This article is based Landsat7ETM+ panchromatic image to the Grand Canyon Town, Lin' an City, Zhejiang Province, for the study area, genetic algorithm-based remote sensing
SeparativeCriterion
- 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。 -Feature selection and feature extraction task is to find a set of classification of the most effective
Rough-Set-Attribute-Reduction
- 基于粗糙集的特征选择Matlab源程序。-Feature selection based on rough set.
Kuschner-BayesianNetwork-feature
- Kuschner论文，贝叶斯网络方法在质谱数据特征选择。其中关于机器学习中贝叶斯分类器部分有完整原理分析，可以用于认知无线电网络的频谱感知等新领域。含有matlab程序大于100页，子函数很多。-Kuschner paper, Bayesian network methods of feature selection in mass spectrometry data. One of the Bayes classifier machine learning part of a complete
ga
- 基于遗传算法和距离的特征选择，用于人工智能和模式识别，进行降维-Distance based on genetic algorithms and feature selection for artificial intelligence and pattern recognition, dimensionality reduction
pr_basic_code
- 模式识别基本方法matlab源代码，包括最小二乘法、SVM、神经网络、1_k近邻法、剪辑法、特征选择和特征变换-Basic method of pattern recognition matlab source code, including the least squares method, SVM, neural networks, 1_k neighbor method, the clip method, feature selection and feature transformati
fs_sup_fisher_score
- fisher score,用于特征选择的方法-fisher score,a method can be used for feature selection
PCA-and-MatlabCode
- 主成分分析法实现特征选择，里面有非常详细的算法介绍，还有一个现实实例介绍，非常具象，里面贴有实现算法的matlab代码-Principal component analysis （PCA）to achieve feature selection , which has a very detailed descr iption of algorithms , there is a real example to illustrate , very concrete , which is affix
fselect
- SVM 特征选择PYTHON 程序，经测试可以用-SVM FEATURE SELECT
features-dimensionality-reduction
- 特征降维方法，其中包含有典型的特征组合方式——PCA和特征选择中的SFFS，SBS，SFS。共四类常用的特征降维方式。-different features dimensionality reduction methods.
SVMRFE
- svmrfe 特征选择 后向排序 svm 数据挖掘 机器学习-Svmrfe after feature selection to sort SVM data mining machine learning
relief
- relief 特征选择 机器学习 数据挖掘 特征权重-Relief feature selection machine learning data mining feature weights
TextFeatureSelectionAlgorithm
- 在文本挖掘中，文档通常以特征向量的形式表示。为了提高文本挖掘算法的运行速度，降低占用的内存空间，过滤掉不相关或相关程度低的特征，提出一种改进的特征选择算法，该算法对特征进行综合考虑，从而更加准确地选取有效的特征。实验验证了改进算法的可行性和有效性。-In text mining，documents are usually meanwith the form of the eigenvector．In order to enhance the operating speed and red
test
- 引入能直接处理连续型数据的邻域粗糙集约简模型，给出一种基于邻域粗糙集模型和粒子群优化的特征选择算法。仿真实验结果表明该算法可以选择较少的特征，改善分类的能力。-employs the neighborhood rough set reduction model which can process the numerical features directly without discretization. Then the particle fitness function in particl
QuickSortOrderReduct
- 引入能直接处理连续型数据的邻域粗糙集约简模型，给出一种基于邻域粗糙集模型和粒子群优化的特征选择算法-Introduce neighborhood rough set reduction model can deal directly with continuous data, given the feature selection algorithm based on neighborhood rough set model and particle swarm optimization
Fitting_with_MATLAB_1_
- 检查/剪裁的例子 孤立点检测实例 正交回归的例子 单因数变异数(泊松回归/逻辑回归)的例子 鲁棒回归的例子 特征选择的例子 常见的边坡问题的例子 -Censoring/clipping example Outlier detection example Orthogonal regression example GLM (Poisson regression/logistic regression) example Robust regress