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NaiveBayes.java.tar.gz 基于weka的分类算法
- 基于weka的分类算法，用于weka拓展应用。朴素贝叶斯模型发源于古典数学理论，有着坚实的数学基础，以及稳定的分类效率。同时，该算法所需估计的参数很少，对缺失数据不太敏感，算法也比较简单。理论上，与其他分类方法相比具有最小的误差率。,Based on the classification algorithm weka, weka develop applications for. Naive Bayes model originated in the classical mathematical
classifier
- 在java中运用weka中的随机森林算法实现的分类器的代码-The use of weka in java in a random forest classifier algorithm code
weka-src
- Java 编写的多种数据挖掘算法 包括聚类、分类、预处理等-Java to prepare a variety of data mining algorithms, including clustering, classification, preprocessing, etc.
weka-3-6-0jre
- Data Mining Software in Java
EM.java.tar
- EM 算法是 Dempster，Laind，Rubin 于 1977 年提出的求参数极大似然估计的一种方法，它可以从非完整数据集中对参数进行 MLE 估计，是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据，截尾数据，带有讨厌数据等所谓的不完全数据(incomplete data)。需要weka的算法包支持。-EM algorithm is Dempster, Laind, Rubin in 1977 for the parameters proposed by maximum
MakeDensityBasedClusterer.java.tar
- 基于局部搜索能力强、收敛速度快的特点,首先初始化一个没有子种群的全局种群,再在全局种群中采用迭代搜索,并对其中的个体进行聚类,当聚类簇中的个体数目达到规定的最小规模时形成一个子种群,然后在各子种群中进行迭代搜索并重新进行聚类,从而提高进化过程中种群的多样性,增强算法跳出局部最优的能力.该算法基于weka，用于weka拓展功能，需要 weka算法包支持。-Based on the local search ability, the characteristics of fast convergen
RandomizableClusterer.java.tar
- 该算法是对weka算法包功能的拓展，是聚类算法中的随机聚类分析。需要weka算法包支持。-The algorithm is a function of the weka package expansion algorithm is stochastic clustering algorithm in cluster analysis. Package to support the needs of weka algorithm.
BayesNet.java.tar
- 贝叶斯网络是一种概率网络，它是基于概率推理的图形化网络，而贝叶斯公式则是这个概率网络的基础。贝叶斯网络是基于概率推理的数学模型,所谓概率推理就是通过一些变量的信息来获取其他的概率信息的过程，基于概率推理的贝叶斯网络(Bayesian network)是为了解决不定性和不完整性问题而提出的，它对于解决复杂设备不确定性和关联性引起的故障有很的优势，在多个领域中获得广泛应用。本算法用于weka算法包的拓展。-Bayesian network is a probabilistic network, wh
RoughSet
- 可嵌入weka 的粗糙集分类算法程序 -Can be embedded in the rough set classification algorithm weka program
CODB
- 基于WEKA的异常检测源代码,JAVA语言编写，可自行开发插件-outlier detection source code based on WEKA
Weka_developping
- WEKA实现了数据挖掘 对于它在JAVA当中的使用 本文有了一些概述-WEKA data mining to achieve it in JAVA for the use of which has some overview of this article
jBNC
- jBNC is a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications. jBNC
MessageClustering
- 用java实现的应用了weka包的Kmeans方法的文本聚类程序。-a program written in java with simplekmeans in weka.jar.
weka-3-6
- weka是用java编写的开源数据挖掘平台，与《数据挖掘：实用机器学习工具与技术》一书配套，特别适合于数据挖掘初学者-weka is an open source data mining plateform, which assort with the book named Data Mining:Practical Machine Learning Tools and Techniques, it is particularly suitable for abecedarian in data
wekaTest
- 一个在java中调用weka算法的演示程序-Call weka algorithm demo program in java
WEKA-Rebuild
- java中集成weka的功能界面，可直接在java中使用weka的所有功能-java in the integration of the functions of the weka interface, can be directly used in java weka all
wekaclassalgos1.8-src
- weka java FILE WITH THE JAVA CODE AND HAVING CODE WRITTEN IN JAVA
KNN-Java-Code
- 1NN的Java源代码，存在于weka环境下，weka是一款很好的数据挖掘工具。-1NN Java source code exists in the weka environment, weka is a very good data mining tools.
distributedWekaBase1.0.2
- extension in java for weka
2014发表论文的规定to吴继芳
- svm in Java for Weka plateform , it works well and can be installed by the menegement of main interface.