搜索资源列表
kmeans
- k-means算法是文本聚类经典算法，也是数据挖掘十大经典算法之一。k-means算法Java实现。-k-means algorithm is a classical algorithm text clustering, data mining is one of the ten classic algorithms. k-means algorithm is implemented in Java.
nlp
- 基于贝叶斯网络的网络评论情感分类，Java实现，内附评论数据包-Based on Bayesian Network Web reviews sentiment classification, Java implementation, the packet included a review
svm
- svm 分类算法 java源代码 很好的学习程序-svm classification algorithm java source code is a good learning program
DataMiningApriori
- apriori的java实现，写的有点长，不能输出关联规则。经测试，可用。-apriori achieve the java, write a bit long, you can not output association rules. Tested and available.
kmeans_demo
- 简单的k-means算法采用java语言实现，具有很高的学习价值-Simple k-means algorithm, using java language, learning a great help
decisionTree
- 决策树java源代码。包含两个决策树算法的代码和一个贝叶斯算法的代码。-Tree java source code. The code consists of two decision tree algorithm and a Bayesian algorithm code.
DBScan03
- DBScan算法实现，用Java高级编程语言正确实现DBSCAN算法，DBScan是一种基于密度的聚类算法，它有一个核心点的概念：如果一个点，在距它e的范围内有不少于MinP个点，则该点就是核心点。核心和它e范围内的邻居形成一个簇。在一个簇内如果出现多个点都是核心点，则以这些核心点为中心的簇要合并。最终输出找到的簇及其数据点。-DBScan algorithm, using high-level programming language Java is implemented correctly
N_DFA
- 这个何不错哦 这个何不错哦 这个何不错哦 这个何不错哦 这个何不错哦 -this is a very good code for java, i spent much on it
literature
- 对采集的专家文献进行分类的一个自写的Java代码-The collection of the expert literature to classify a self written Java code
decisionTree
- 一个决策树的java实现版本，用于实现对离散和连续问题两种问题- Java implementation of a decision tree version, for the realization of discrete and continuous problems of two kinds of problems
FPGrowth
- FpGrowth算法的Java完整实现，可用于改进到分布式环境，自制基础数据文件后结果可生成-Results can generate a full implementation of Java FpGrowth algorithm that can be used to improve the distributed environment, homemade basic data files
itemcf
- Hadoop平台上的物品协同过滤程序，使用Java语言编写(A Item Collaborate Filter Program based on Hadoop platform written by Java)
java网络爬虫
- 是一个无须配置、便于二次开发的JAVA爬虫框架（内核），它提供精简的的API，只需少量代码即可实现一个功能强大的爬虫(Is a JAVA reptile framework (kernel) that does not need to be configured for easy development. It provides a streamlined API that requires a small amount of code to implement a powerful crawl
基于粗糙集的层次聚类算法研究
- 实现了两种基于粗糙集模型的层次聚类算法，采用java编程语言实现(Hierarchical clustering algorithm for categorical data using a probabilistic rough set model)