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  1. 编程语言:所有
  2. 代码类别:数据挖掘
  3. 发布时间:一年内
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1. qb神经网络

  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.)

2
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171
浏览
2020-06-23发布

2. QB模型 神经网络

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.)

11
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163
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2020-06-23发布

3. Archive

  PCA 数据降维 PTYTHON 数据分析/挖掘(PCA dimensionality reduction data mining/analysis)

1
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166
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2020-06-21发布

4. Archive

说明:  PCA 数据降维 PTYTHON 数据分析/挖掘(PCA dimensionality reduction data mining/analysis)

2
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172
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2020-06-21发布

5. 贝叶斯网络 R语言实例 牛津大学

说明:  R语言构建贝叶斯网络,很实用的讲解和案例(Construction of Bayesian network with R language, a very practical explanation and case)

1
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185
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2020-06-19发布

6. 粗糙集

  粗糙集在进行属性约简时需要求其正域,此为求正域程序(Rough Set for Positive Domain)

3
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157
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2020-06-19发布

7. 粗糙集

说明:  粗糙集在进行属性约简时需要求其正域,此为求正域程序(Rough Set for Positive Domain)

2
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170
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2020-06-19发布

8. 聚类指标小结

  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.)

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205
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2020-06-19发布

9. 聚类指标小结

说明:  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.)

9
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148
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2020-06-19发布

10. 用matlab 实现了kmeans算法

  用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

0
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153
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2020-06-19发布

11. KMeans

说明:  用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

9
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142
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2020-06-19发布

12. Kares入门资料打包

  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.)

0
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160
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2020-06-17发布

13. Kares入门资料打包

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.)

5
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171
浏览
2020-06-17发布

14. boxcox

  boxcox函数的python实现,引用该函数可将偏态分布调整为正态分布(Python implementation of box Cox function)

0
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165
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2020-06-17发布

15. boxcox

说明:  boxcox函数的python实现,引用该函数可将偏态分布调整为正态分布(Python implementation of box Cox function)

1
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193
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2020-06-17发布

16. Python for Data Analysis

  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.)

2
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188
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2020-06-16发布

17. Python for Data Analysis

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.)

3
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156
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2020-06-16发布

18. 0406遗传算法优化神经网络

说明:  基于股票数据的神经网络,关于结算的预测,通过遗传算法加以改进(Based on the neural network of stock data, the prediction of settlement is improved by genetic algorithm)

4
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148
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2020-04-26发布

19. DataMiningProject-Bearing

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)

5
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142
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2020-04-12发布

20. classification_toolbox

说明:  多种基本分类训练,包括支持向量机,偏最小二乘,主成分分析和线性分析(A variety of basic classification training, including support vector machine, partial least squares, principal component analysis and linear analysis)

2
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152
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2020-03-10发布