搜索资源列表
AGENES
- 使用Java实现AGNES聚类算法，内存要求较高，数值误设置过大-AGNES clustering algorithm using the Java implementation, high memory requirements, numerical error is set too large
cure_cluster
- java语言编写的Cure聚类算法，实现对数据点的聚类-java language Cure clustering algorithm to achieve the clustering of data points
DBSCAN_cluster
- java语言编写的 DBSCAN基于密度的聚类算法，可实现对数据点基于密度的聚类-java language DBSCAN density-based clustering algorithm can be realized on density-based clustering of data points
REDBSCAN_cluster
- 使用myeclipse打开 关于Redbscan的聚类算法，可以实现对数据点的聚类-Use myeclipse open about Redbscan clustering algorithms, data points can be achieved on clustering
Kmeans
- K-均值聚类算法，是一种随机选取数个数据中心进行点聚类处理进而生成分类的数据挖掘算法，具有很好的学习功能。-K-means clustering algorithm is a randomly selected number of data center point clustering process thereby generating classification data mining algorithms, with good learning function.
textcluster
- Text Clustering, Kmeans Cluster Stop word Handler TermVector TFIDFMeasure Tokeniser
src
- 聚类算法，包括ISOdata以及K-Means。在实验报告中详细分析了一下实验的结果-Clustering algorithms, including ISOdata and K-Means. In a detailed analysis of the experimental report about the results of the experiment
kmeans_report
- Java 实现k-means 聚类算法，分别以迭代次数及分配不再发生变化为算法终止条件，用图片作为数据集，比较运行时间-Java implementation of k-means clustering algorithm, respectively, and the distribution of the number of iterations of the algorithm terminates no change in the conditions, with a picture (o
Kmeans
- k均值聚类算法代码, k均值聚类算法代码-k-means clustering algorithm code, k-means clustering algorithm code
kmeans
- 简单的k_means聚类算法,用java语言编写实现，扩展性不强-simple kmeans clustering method
kmeans
- 这是一个kmeans算法 实现了聚合分类功能-Kmeans algorithm for clustering
Cluster-Building
- Clustering Large Probabilistic Graphs
DensityBasedClustering
- Density based clustering with GUI
_k_means_picture
- K-means聚类算法 用于图像处理 JAVA语言编写，聚类中值算法可运行-k-means clustering algorithm image processing
NlPIR
- 实现了中文分词，我还自己加入了if-idf和聚类。-Achieve a Chinese word, I myself joined the if-idf and clustering.
text_example
- text matching and clustering code in java
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.
CBIR
- Content based image retrieval in java using k-means clustering and haar wavelet transform
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
K_Means
- k-means 算法的工作过程说明如下：首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作为标准测度函数. k个聚类具有以下特点：各聚类本身尽可能的紧凑，而各聚类之间尽可能的分开。下面给出我写的源代码。-work process k-means al