rdqern

自动生成Excel表格，包括测量系统分析MSA GR&R--均值极差法 ,方差分析，均值极差(Automatic generation of Excel tables, including measurement system analysis MSA GR&R - mean extreme difference method, variance analysis, mean extreme difference)

分类器的性能比较与调优: 使用scikit-learn 包中的tree，贝叶斯，knn，对数据进行模型训练，尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较，分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.)

说明：  偏最小二乘回归！PLSR，可用于解决一些回归问题！(Partial least squares regression! PLSR can be used to solve some regression problems!)

利用python调用新浪api接口实现的新浪微博数据的挖掘，能够获取指定的经纬度地点的微博动态信息，还能够将其写入MySQL数据库中。

说明：  从数据库获取车辆在一段时间内的所有行驶记录的相关数据，确定所需数据为GPS经纬度坐标和驾驶时长等，QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离，两条轨迹需要具有相同的经纬度点数，具有相同点数的轨迹最大的优点是对轨迹距离成对计算，且相同轨迹之间具有更高的分辨率，对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)

运用支持向量机对一组超宽带非视距信号识别(Support Vector Machine Signal Identification)

波形设计算法，阵列信号处理等相关知识的介绍仿真等(Introduction and Simulation of waveform design algorithm, array signal processing and other related knowledge)

数据挖掘中编写C语言程序数据预处理，读取文本文件中的数据，使用链表，并输出该组数据的按平均值、中值、边界值平滑的结果。若分箱时数据缺失则用最后的值复制代替，还要找出程序中的离群点，要求程序符合结构化程序设计风格，关键地方需加注释。完美实现！

应用python编写的百度指数新闻爬取代码(baiduindex spider)

聚类评价指标的各种说明，非常详细，请仔细阅读。(Cluster evaluation indicators of various descriptions, very detailed.)