资源列表
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
AI-Naive
- 利用Python实现朴素贝叶斯分类方法。实现程序具有普适性，同时附带测试数据。可以直接运行。-Python implementations utilizing Naive Bayes classification. Achieve universal program has also included with the test data. It can be run directly.
rvm-wind-power-forecast
- 相关向量机用于风电场功率预测和各种大数据分类问题，单变量输出-Relevance vector machine for a wind farm power prediction and a variety of large data classification problem, univariate output
distanceKNN
- 可以分别设置度量距离的KNN分类器，有欧式和马氏距离。对模式识别十分重要的作用，有着较好的分类效果，可以帮助新手更好的理解KNN原理，对人脸识别有着很好的演示作用。-Distance can be set respectively KNN classifier, style and markov distance. For pattern recognition is an important role, has a good classification effect, can help be
cnbeta
- 运用python爬取cnbeta的最新内容，运用到了scarpy模块。-The use of python crawl cnbeta the latest content, the use of the scarpy module.
K-means-Ensemble
- 该算法是基聚类算法为K-means，然后再进行聚类集成，方法为投票法-The algorithm is based on clustering algorithm for K-means, and then the clustering ensemble, method for voting
kmeansCluster
- 开源搜索Carrot2中的kmeans聚类算法（作为性能对比用），由波兰学者Osinski撰写。-The open source search Carrot2 kmeans clustering algorithm (used as a performance comparison), written by the Polish scholar Osinski.
roughset-into-weka
- 可以嵌入weka中的粗糙集约简算法，进一步扩充weka的数据挖掘功能-Weka can be embedded in the rough set reduction algorithm to further expand weka data mining functions
BayesClassify
- Requirements : 1) function fileOpen (user written) to open files : also uploaded 2)function strsplit1 also uploaded 3)training data, also uploaded
dbscanamatlab
- dbscan的matlab实现，dbscan密度聚类算法的快速实现聚类，计算速度有所加快，能快速聚类。-dbscan matlab realize, quickly realize clustering dbscan density clustering algorithm to calculate the rate has accelerated, rapid clustering.
decision-making-tree
- 决策树的Python代码实现，要所报内含原数据-Decision Tree Python code, containing the original data to be reported
globle_kmeans
- 全局k-means算法，可有效解决传统k-means算法受初始点影响的缺陷，该方法可获得数据稳定的聚类结果。