这个问题有点偏执,就像在谷歌搜索结果混合了音频和傅里叶变换等。
from imblearn.over_sampling import SMOTE
sm = SMOTE(random_state=12, ratio = 1.0)
x_train_res, y_train_res = sm.fit_sample(X_train, y_train)
但最近,我遇到了
sm = over_sampling.SMOTE(random_state=12, ratio = 1.0)
x_train_res, y_train_res = sm.fit_sample(X_train, y_train)
有什么不同?from imblearn.over_sampling import SMOTE
sm = SMOTE(random_state=12, ratio = 1.0)
和
import imblearn.over_sampling
sm = over_sampling.SMOTE(random_state=12, ratio = 1.0)
是相同的。唯一的区别是您如何访问代码中的SMOTE函数。