传递熵传递时间计算

说明：  利用python进行数据分析，英文书籍，从pandas库的数据分析工具开始利用高性能工具对数据进行加载、清理、转换、合并以及重塑；利用matpIotlib创建散点图以及静态或交互式的可视化结果；利用pandas的groupby功能对数据集进行切片、切块和汇总操作；处理各种各样的时间序列数据。(Starting from the data analysis tools of pandas database, high performance tools are used to load, clean, transform, merge and remodel data; scatter plots and static or interactive visualization results are created by matpIotlib; data sets are sliced, sliced and aggregated by pandas group by function; and various operations are processed. Time series data.)

数据挖掘中的binning算法，用于数据预处理(Binning algorithm in data mining for data preprocessing)

徐士良《C常用算法程序集》第2版 第2部分()

说明：  将数据集转换为拉普拉斯矩阵，然后利用基于图论的谱聚类进行聚类。拉普拉斯矩阵采用高斯核函数，全连接方法计算。谱聚类擅长处理高维数据或非凸数据集。(The data set is transformed into Laplacian matrix, and then clustered by spectral clustering based on graph theory. The Laplacian matrix is calculated by using the Gauss kernel function and the full connection method. Spectral clustering is good at dealing with high-dimensional or non-convex data sets.)

说明：  一个用python实现的PCA算法，并且给了简易素材(A PCA algorithm implemented in python, and gave a simple material)

关于大数据的论文，对稀疏表示分类有很大的帮助，希望对初学者哟帮助

在linux 下C语言实现最近邻聚类算法，工程已经使用(near K neighbor cluster)

说明：  用于轴承大数据的故障诊断和数据挖掘，可将轴承的振动信息进行数组分析，获得预测模型，准确率较高(It can be used for fault diagnosis and data mining of bearing big data. It can analyze the vibration information of bearing by array and obtain the prediction model with high accuracy)

说明：  深度学习框架Keras入门资料，里面的代码包括课件和DEMO有利于新书入门学习，简单易懂(Keras Introductory Information of Deep Learning Framework, which includes courseware and DEMO, is helpful for introductory learning of new books. It is easy to understand.)

零件切割问题 回溯算法的实现, 给定一块宽度为W的矩形板,矩形板的高度不受限制,现需要从板上分别切割出n个高度为hi,宽度()