搜索资源列表
LDA
- 线性判别分析（LDA）用于特征选择，可以对数据集或者图像提取有用特征，用于分类或者聚类等机器学习应用中-Linear Discriminant Analysis (LDA) for feature selection, application in dataset or image feature extraction, for classification or clustering applications in machine learning
NJW
- NJW算法，普聚类算法，利用3种拉普拉斯矩阵，作用在自制的数据集上-failed to translate
art
- 用VC++编写的自适应谐振网络（ART）模型的源代码，用于将二值数据集进行无师聚类。-This program contains code implementing the adaptive resonance theory(ART) network. Source code may be found in ART.CPP.
FCMClust
- 采用模糊C均值对数据集data聚为cluster_n类-Using Fuzzy C-Means dataset data gathered for cluster_n classes
2D-LDA
- LDA是一种线性降维方法，对原有的高维人脸数据集降维，然后识别，具有很好的聚类和识别效果。有详细的说明-LDA is a linear dimensionality reduction method, the original high-dimensional face data set dimensionality reduction, and then identify clustering and identification. Described in detail
Fuzzy-c-means-clustering-algorithm-
- k均值算法是模式识别的聚分类问题，采用模糊C均值对数据集data聚为cluster_n类 -k-means algorithm is a pattern recognition poly classification,by using Fuzzy C-Means data sets, data gathered cluster_n class
PAM
- 利用欧式度量聚类真实数据集和实际数据集用于对各类数据分类 -European metric clustering real data sets and real data sets for various types of data classification
Desktop
- 欧式距离PAM聚类算法，利用欧式度量聚类真实数据集和实际数据集用于对各类数据分类-Euclidean distance the PAM clustering algorithms using the European metric clustering real data sets and real data sets for the various types of data classification
kmeans
- 基于mailab iris数据集的kmeans聚类，适于matlab及聚类分析的入门学习-failed to translate
FCM
- 基于matlab iris数据集的FCM（模糊C）聚类，适于matlab和聚类分析的入门学习。-failed to translate
chameleon-data.tar
- 这个是cluto的数据集。用它可以测试该项目的聚类性能。-This data set is cluto. You can use it to test the clustering performance of the project.
isolet5
- isolet5数据集，已处理成.mat格式，包括数据和类标，用于机器学习，聚类，分类等问题的研究-isolet5 dataset has been processed to study mat form, including data and class standard, machine learning, clustering and classification problems
sonar
- sonar数据集，已处理成.mat格式，包括数据和类标，用于机器学习，聚类，分类等问题的研究-sonar dataset has been processed to study mat form, including data and class standard, machine learning, clustering and classification problems
Fuzzyjulei
- 聚类分析，模糊集，适用于多维数据聚类。在研究生期间所做的成功，成功将三位数据实现聚类，并把它运用到交通分类当中。-Cluster analysis, fuzzy sets, is applicable to multi-dimensional data clustering.During the graduate student success, success will be three data clustering, and apply it to the classification o
k_means
- K-mean 算法是 J.B.MacQueen 在 1967 年提出的，是到目前为止应用最广泛最成熟的一种聚类分析方法。因该算法具有简单快速、适于处理大数据集等优点，目前，已被广泛应用于科学研究和工业应用中。-K-mean algorithm is JBMacQueen proposed in 1967, is by far the most mature and most widely used of a clustering analysis. Because the algorithm i
k-means-iris
- 运用k-means算法对IRIS数据集进行聚类分析-K-means algorithm is appliled to do cluster analysis for IRIS dataset.
kde
- 核密度估计,matlabkernel density estimation是在概率论中用来估计未知的密度函数，属于非参数检验方法之一，由Rosenblatt (1955)和Emanuel Parzen(1962)提出，又名Parzen窗（Parzen window）。Ruppert和Cline基于数据集密度函数聚类算法提出修订的核密度估计方法。-kernel density estimation
BOVW_Class_DEMO
- Matlab实现BOVW模型，特征提取采用SIFT算法，字典学习采用k-means聚类学习，数据集采用UCM21类分类信息-Matlab achieve BOVW model, feature extraction algorithm using SIFT, dictionary learning using k-means clustering, data collection using UCM21 class category
Fcm
- 采用FCM(模糊C均值)算法将数据集data聚为cluster_n类(FCM (fuzzy C means) algorithm is used to aggregate the data set data into cluster_n class)
多视图聚类代码
- 里面自带两个数据集，可以正常运行出结果图。