搜索资源列表
GAACO.rar
- genetic algorithm combine Ant colony optimization for feature selection,genetic algorithm combine Ant colony optimization for feature selection
mrmr-ftest.zip
- This is a code for feature selection. Which combines minimum redundency and max relevance and Ftest. Originally it is written for gene selection but can be used for any kind of feature selection.,This is a code for feature selection. Which combines m
mRMRFeatureSelection
- mRMR_0.9_compiled最小冗余和最大相关特征选取源代码，-This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method, whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent pu
FeatureSelection
- Feature Selection using Matlab. The DEMO includes 5 feature selection algorithms: • Sequential Forward Selection (SFS) • Sequential Floating Forward Selection (SFFS) • Sequential Backward Selection (SBS) • Se
AdaptiveFeatureSelectionforHyperspectralDataAnalys
- 高光谱数据分析中的自适应特征提取算法adaptive feature selection-Hyperspectral data analysis adaptive feature extraction algorithm adaptive feature selection
tezhengxuanzhe
- 利用最小互信息实现向量的特征选择，优化分类器的设计，原创-The use of mutual information to achieve the smallest feature selection vectors, optimizing the classifier design, originality
Bolasso-feature-selection-prediction
- 这个程序实现了Francis R. Bach的Bolasso算法，用于特征选取和预测。主要用于高纬度问题的特征选取，它使用了带有Bootstrap方法的自助抽样的正则化回归，并使用了Karl Skoglund的lars实现。-This procedure achieved Francis R. Bach s Bolasso algorithms for feature selection and forecasting. The main problem for high-latitude fe
Collaborativefuzzyclusteringmodel
- 协同模糊聚类建模通过特征选择和协同模糊聚类的模糊建模方法构建T-S模型，并用此模型对数据进行测试。-Collaborative fuzzy clustering modeling and collaboration through the feature selection fuzzy clustering TS fuzzy modeling method to build models and use this model of data for testing.
featureselection
- 基因算法实现的特征提取，实现平台是matlab-feature selection with genetic algorithm
Verver_FS_Version_5.1.6
- Feature Selection using matlab
IEEEXplore-4.pdf
- Mutual Information Feature Selection
2005S9568
- feature selection from iris data set it will use statistical methods and get the best set of features then use graphs to classify the data-feature selection from iris data set it will use statistical methods and get the best set of features then us
wenj
- adaboost FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION-FEATURE SELECTION USING ADABOOST FOR FACE EXPRESSION RECOGNITION
patternRecognition
- 这系列课件系统地讲述了模式识别的基本理论和基本方法。内容涵盖了贝叶斯决策、概率密度函数的估计、线性判别函数、邻近法则、特征的选择和提取、非监督学习、神经网络、模糊模式识别等。-This series of courseware on a pattern recognition system to the basic theory and basic methods. Covers the Bayesian decision-making, the estimated probability de
FeatureSelectiom
- this file is for feature selection
PresentationPro_FreeSample.ZIP
- this file is for feature selection
Derya_Ozkan
- Feature Selection for Face Recognition Using a Genetic Algorithm
Rapid_Object_Detection
- A very fast and robust object detection framework. A very simple set of Haar like box features A commensurating Image representation (that enables fast calculation of features, feature scaling and normalization) Efficient feature selectio
Patternrecognition
- 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 network, 1_k neighbor method, editing method, feature selection and feature transformatio
Feature Selection matlab toolbox
- It's a Matlab toolbox designed by ASU. It is easy to use and you can use it to achieve the feature selection, classify and so on.