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隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)

求解矩阵的最大最小特征值及对应的特征向量,以及计算条件数()

说明：  Python数据预处理示例，包括数据清洗、数据整合、数据变换等操作。(Python data preprocessing examples, including data cleaning, data integration, data transformation and other operations.)

一个很实用的采用Neville算法的拉格朗日插值程序,(A very practical Lagrange interpolation program using Neville algorithm,)

时间序列法，通过过去数据来建立相应模型来预测未来数据(Time series, using past data to establish corresponding models to predict future data)

weka是一个很优秀的数据挖掘软件，可以把weka作为程序包打入工程中，基本想要的功能很快就能实现

该程序用于分类，用到的算法是Bagging and Knn 两种算法(This program is used for classification, the algorithm used is bagging and knn two algorithms)

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.)

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)

Python数据预处理示例，包括数据清洗、数据整合、数据变换等操作。(Python data preprocessing examples, including data cleaning, data integration, data transformation and other operations.)