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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)

周志华 机器学习 第三章 python 参考答案(Zhou Zhihua machine learning third chapter Python reference answer)

数据挖掘经典算法，频繁项集挖掘经典算法，CFPGROWTH算法，JAVA实现，代码中有详细注释

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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.)

用C++实现各种排序算法：如冒泡排序,选择排序,插入排序,希尔排序,快速排序,归并排序,基数排序和堆排序,并带有源代码说明()

多重分形去趋势波动分析法，用于不同时间序列的重分形交叉相关性分析。(Multifractal detrended fluctuation analysis)

插值抽取的内容,数字变频用, 分享了,请高手完善指教,()

一个xgboost实现的回归模型预测，数据集来源于kaggle的taxi竞赛(Regression model prediction based on a xgboost implementation)

聚类分析31省市的经济情况，以每个聚类簇的平均值来衡量省市经济的发展水平。(Cluster analysis of the economic situation of 31 provinces and municipalities, with the average value of each cluster to measure the level of economic development of provinces and municipalities.)