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[freeScience.ir]-10.1109-GreenTech.2013.46
- the attached file is about data mining
[freeScience.ir]-10.1109-PESGM.2012.6345278
- the second file is about data mining
[freeScience.ir]-10.1109-TDC.2014.6863174
- the third file is about data mining in stream clustering
[freeScience.ir]-10.1109-TSG.2014.2313724
- the forth file is about data mining
[freeScience.ir]-10.1109-TSG.2015.2399974
- the fifth file about data mining
Desktop
- K均值聚类算法，对风电机组功率数据进行聚类分析，包括详细的程序说明。 只要把这两个文件放入一个空文件夹下，在MATLAB中执行m文件，就可得到聚类结果。-K-means clustering algorithm, the wind turbine power data clustering analysis, including a detailed descr iption of the procedures. As long as these two files into an empt
kmeans
- kmeans算法，简单实现，文件读入，读入文件为txt，数据用逗号隔开-kmeans algorithm, simple implementation, file reads, reads the file as txt, data separated by commas
plot_svm_anova
- plot_svm_anova机器学习中大数据挖掘python文件-Machine learning cuhk python file data mining
Jason211
- 从Jason2卫星的nc文件中提取测高数据进行网格化处理 1*1 -Extract altimetry data Jason 2 satellite nc mesh file processing* 1 1
findKN
- 在数据挖掘、人工智能等领域中，都常用到KD树来进行K近邻查找。本程序是自己用C++实现的一个KD树来进行的K近邻查找程序，包含建树和查找。文件中附有测试文件。-In data mining, artificial intelligence and other areas, it is commonly used to KD tree to find K nearest neighbor. This procedure is K neighbor Finder C++ they used to a
code_BPMF
- 如何使它工作： 1。创建一个单独的目录，并将所有这些文件下载到相同的目录中 2。下载7个文件： *demo:主文件demo:PMF和贝叶斯PMF * PMF.m:训练的PMF模型 * bayespmf.m贝叶斯PMF模型实现吉布斯采样器。 * moviedata.mat样本数据包含三元组（user_id，movie_id，评分） * makematrix.m：辅助功能转换成大型矩阵的三元组。 * PRED.m:辅助功能使得预测验证集。 三.在Matlab只需运
Data-dimensionality-reduction
- 该压缩文件为部分数据降维方法，有LTSA、HHLLE、ISOMAP、LLTSA、LLP-The compressed file for the partial data dimensionality reduction method, there are LTSA, HHLLE, ISOMAP, LLTSA, LLP
find
- 从excel中读取所需文档的数据，并写进相对位置，对名称进行文件路径字符串拼接-From the excel to read the required document data, and write the relative position, the name of the file path string stitching
data
- 训练NER的语料文件，已全文标注，四个字段(Training NER's corpus file, full text annotation, four fields)
LDA_ FDA_with_tutorial
- LDA降维是常用的降维手段之一，是常用的有监督学习降维工具。这个文件对其产生W后的使用进行了简要说明，使用W进行最终的降维可以得到十分漂亮的分析结果（在数据分布符合假设分析的情况下。）(LDA dimension reduction is one of the commonly used dimensionality reduction methods. It is a commonly used supervised learning dimensionality reduction tool