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K-meanCluster
- How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the f
pic_usb
- pic usb source code samples
mapred
- hadoop mapreduce测试样例，文档，源码-hadoop mapreduce test samples, documentation, source code
ipp-samples
- 英特尔的ipp程序demo，可进行多核编程，运行效率大幅提升。-Intel' s ipp program demo, can be multi-core programming, significantly increasing operating efficiency.
MPIch-KNN
- 基于MPICH的KNN并行化计算，固定5个进程同时计算，经24W个训练样本学习，预测效果良好.-MPICH-based KNN parallel computing, fixed five processes simultaneously calculated by 24W training samples to learn, good prediction.