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cengcijulei
- 层次聚类算法与之前所讲的顺序聚类有很大不同，它不再产生单一聚类，而是产生一个聚类层次。-Hierarchical clustering algorithms and sequence clustering before talking about is very different, it is no longer produce a single cluster, but does generate a cluster level.
textcluster
- 基于KMeans的文本聚类算法，支持文本输入，简单易懂-KMeans clustering algorithm based on text, support for text input, easy to understand
SCAN
- SCAN算法，从超大图中分割出密集的结构聚类算法-SCAN algorithm, split a dense structure from large graph clustering algorithm
K_average
- 数据挖掘中聚类算法的K_均值算法，采用文件输入数据形式，找到相关聚类-Data mining clustering algorithm K_ means algorithm, using the form input data file, find the relevant clustering
DBSCAN
- 基于密度的密度聚类算法，该算法的结果可以聚成任意的形状。-Density clustering algorithm based on density, the result of the algorithm can be clustered into arbitrary shape.
k-Means
- k-means算法的java实现，自动聚类算法。是基于距离来进行聚类-k-means algorithm to achieve the java automatic clustering algorithm. Based on the distance to the cluster
KmeanProject
- 利用k均值聚类算法对词进行聚类,基于最大最小原则初始化质心-cluster word by kmeans
CanopyExm
- Canopy聚类算法是一个将对象分组到类的简单、快速、精确地方法。每个对象用多维特征空间里的一个点来表示。这个算法使用一个快速近似距离度量和两个距离阈值 T1>T2来处理。 Canopy聚类算法能快速找出应该选择多少个簇，同时找到簇的中心，这样可以大大优化 K均值聚类算法的效率 。-Canopy is a clustering algorithm to group objects into simple categories, fast, accurate method. Each obj
Kmeans-java
- Kmeans算法的java实现，能实现大数据集的Kmeans聚类算法的实现-Achieve Kmeans algorithm to achieve the java can achieve large datasets Kmeans clustering algorithm
KMeans
- K-means算法是硬聚类算法，是典型的基于原型的目标函数聚类方法的代表，它是数据点到原型的某种距离作为优化的目标函数，利用函数求极值的方法得到迭代运算的调整规则。-K-means clustering algorithm is hard, is a typical prototype-based clustering method on behalf of the objective function, it is a method of data points to a certain di
iris_php_mean
- iris采用聚类算法分类，php代码实现。iris_train2.php用于训练数据，iris_test.php用于测试数据。-a kind of k-means,php programming
Cluster
- 聚类算法的java实现，包括K-means（基于划分聚类），DBSCAN(基于密度聚类）-Clustering algorithm ， achieved by java, including K-means (based on the division clustering), DBSCAN (density-based clustering)
dbscan
- 基于DBSCAN聚类算法的java源码，可以用于dbscan聚类-DBSCAN clustering algorithm based on the Java source code, can be used for DBSCAN clustering
WawaKMeans
- WawaKMeans的算法实现，用Wawa实现K-means聚类算法与MapReduce实现的算法进行对比-WawaKMeans algorithm implementation, using K-means to achieve Wawa clustering algorithm and MapReduce implementation of the algorithm to compare
Hello
- 聚类算法的Java实现代码（包括运行文件）-Clustering Algorithm Java implementation code
Cluster
- 用Java语言实现isodata的模式识别聚类算法--Java language used to achieve the pattern recognition ISODATA clustering algorith
Cluster---A
- FCMDD聚类算法 Java实现 可处理时间序列数据集，和普通数据集-Quot uMc
FCM_2
- FCM聚类算法，Java实现，对普通数据集进行聚类操作-FCM u802A u7C7B u7B97 u6CD2 uFF0CJava u5B9E u73B0 uFF0C u5BF9 u666E u901A u6570 u636E u96C6 u8FDB u884C u805A u7C7B u64CD u4F5C
Kmeans
- 算法思想：提取文档的TF/IDF权重，然后用余弦定理计算两个多维向量的距离来计算两篇文档的相似度，用标准的k-means算法就可以实现文本聚类。源码为java实现(Algorithm idea: extract the TF/IDF weight of the document, then calculate the distance between two multidimensional vectors by cosine theorem, calculate the similarity
clique
- 使用java为开发语言，基于高维空间网格聚类算法CLIQUE(Use java as the development language, based on high dimensional space grid clustering algorithm CLIQUE)