资源列表
TreeforR
- 自己使用R，语言编写的决策树实现算法，比较容易理解，大家可以-Using the R language to achieve the decision tree algorithm implementation, easier to understand
JavaToTree
- zijizai da si de shi hou 使用java实现的决策树算法,-Using java to achieve the decision tree algorithm
E-Algorithm
- 用于数据挖掘分类的算法，E-Alothm，并附有10个左右的KEEL专用数据集，算法实现+实际例程。-For the data mining classification algorithm, E-Alothm, and with 10 or so KEEL dedicated data set, the algorithm to achieve+ practical routines.
254280176MATLABcar
- 算法的例程，希望对大家的学习工作有所帮助吧。-algorithm routines, we want to learn to help it.
EEMD1
- EEMD算法的例程，希望对大家的学习工作有所帮助吧。-EEMD algorithm routines, we want to learn to help it.
SVM-and-NB
- 支持向量机与朴素贝叶斯算法，对数据进行分类后深度了解数据的结构-Support vector machine and naive Bayes algorithm.Classifying the data and understanding the structure of the data in depth
c25
- 一个探究VC++ 异步通信原理与实例的代码，程序同样是基于C/S结构的，分服务端与客户端，程序运行效果请看截图。-A VC++ asynchronous communication principle and examples of the code, the program is also based on the C/S structure, sub-service and client, the program run the results see screenshots.
Fuzzyclustering
- 基于MATLAB实现的模糊聚类算法，程序包含了多种聚类算法，实验效果较好。-MATLAB based on the realization of fuzzy clustering algorithm, the program contains a variety of clustering algorithms, the experimental results are better.
jibenyiqunjulei
- 该算法，解决了不收敛的问题，聚类效果非常好。改进的蚁群算法是基于遗传算法的改进，在基本遗传算法的基础之上，加入了变异因子，产生变异，从而更快的收敛。-The algorithm solves the problem of convergence, and the clustering effect is very good. The improved ant colony algorithm is based on the improvement of genetic algorithm. O
PCA
- 主成分分析做人脸识别的一个很简单的应用，其中数据集是CMU的一个人脸数据集，数据集和程序打包一起了，其中参数可以修改的，比较粗糙，不过能对PCA做人脸识别有一个大概的认识-The principal component analysis to do a very simple application of face recognition, the data set is a face of the CMU data set, the data set and the package toget
k-means
- java实现kmeans算法，方便数据挖掘相关人员更直观了解整个算法的思想及实现过程-java achieve kmeans algorithm to facilitate data relevant personnel more intuitive understanding of the whole idea of mining algorithms and implementation process
backprop
- 应用深度学习方法，挖掘数据在更深层次上的特征-Application of deep learning method, digging deeper level characteristic data