资源列表
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- python scikit-learn lshforest的使用-use lshforest
big-data
- 介绍了大数据时代的发展以及大数据与大数据在经济学的应用，还有大数据的安全与隐私保护，网络大数据的现状与展望-It introduced the development of big data and big data era of big data applications and economics, as well as large data security and privacy protection, the current situation and prospect of larg
learn_struct_K2
- 本程序是贝叶斯网络结构学习的K2算法程序，可获取离散变量的贝叶斯网络-This procedure is K2 Bayesian network structure learning algorithm program, available discrete variables Bayesian Network
example_DAGlearn
- 程序是基于图论 , 对后验概率提取参数,使得很好的描述贝叶斯网络中变量之间的依赖关系-Program is based on graph theory, the extraction parameters on the posterior probability of such a good descr iption of the dependencies between variables in a Bayesian network
minimum_spanning_tree
- 本程序是基于最小洗漱树的分类器 可得到分类效果不错的分类器-This procedure is based on a minimum wash tree classifier good classification results obtained classifier
Kmeans
- 按照模式识别一书，实现k均值聚类的matlab版本代码-According to the book Pattern Recognition , implement k-means clustering matlab version of the code
kNN
- KNN，k近邻算法，内附测试数据集，机器学习实战源码-KNN, k nearest neighbor algorithm, enclosing the test data set, machine learning practical source
log
- 提出基于拉普拉斯高斯（Laplacian of Gaussian，LoG）算子边缘检测的全局二值化方法对其进行处理，该方法通过提取图像边缘部份的像素灰度获得图像二值化的阈值。处理结果表明，与传统的几种方法相比，该方法能够快速选取良好的二值化阈值，较好地区分目标和背景，在相当大模板宽度内图像二值化的结果都令人满意。-Is put forward based on the Laplacian of Gaussian (LoG) Laplacian of Gaussian, operator edge
readdatajtwc
- 读取印度洋热带气旋的相关信息，包括生成位置，生成数目，生成后轨迹等。-Read Indian Ocean tropical cyclone-related information, including generating position, generation number, after generating trajectory.
large-data
- 对大数据的应用，很有启发负荷预测。我希望你能有所帮助。-Load forecasting on large data applications, very enlightening. I hope you can help.
WordCount2
- 基于hadoop1.x的wordcount程序，jar包是全的，只要设置一下即可使用-a word count program depend on hadoop 1.x with all jar files needed,easy to use
Naive-Bayes.py.tar
- Classification algorithm using Naive Bayes. Written for News Group data set. 99 accuracy-Classification algorithm using Naive Bayes. Written for News Group data set. 99 accuracy!!!