ML之LoR:利用布鲁塞尔的creditcard数据集进行采样处理(欠采样{Nearmiss/Kmeans/TomekLinks/ENN}、过采样{SMOTE/ADASYN})同时采用LoR算法(PR和ROC评估)进行是否欺诈二分类
目录
更新……
- F:\Program Files\Python\Python36\lib\site-packages\matplotlib\axes\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.
- warnings.warn("The 'normed' kwarg is deprecated, and has been "
- 0 284315
- 1 492
- Name: Class, dtype: int64
- Default 方法
- Undersampling RandomUnderSampler 方法
- F:\Program Files\Python\Python36\lib\site-packages\imblearn\under_sampling\_prototype_selection\_nearmiss.py:178: UserWarning: The number of the samples to be selected is larger than the number of samples available. The balancing ratio cannot be ensure and all samples will be returned.
- "The number of the samples to be selected is larger"
- Undersampling NearMissV1 方法
- F:\Program Files\Python\Python36\lib\site-packages\sklearn\svm\_base.py:977: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.
- "the number of iterations.", ConvergenceWarning)
- Undersampling NearMissV2 方法
- Undersampling NearMissV3 方法
- Undersampling ClusterCentroids 方法
- Undersampling TomekLinks 方法
- Undersampling EditedNearestNeighbours 方法
- 数据清洗后大类样本数量
- Original: 227451
- After Tomek Link: 227429
- After ENN: 227326
- Oversampling RandomOverSampler 方法
- Oversampling SMOTE 方法
- Oversampling ADASYN 方法
网站声明:如果转载,请联系本站管理员。否则一切后果自行承担。
加入交流群
请使用微信扫一扫!