在DASK随机化搜索CV中实现SMOTEENN

我成功地在管道中使用SMOTEENN和RF实现了一个模型。这样地:

import random
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import RandomizedSearchCV
from sklearn.metrics import roc_curve, roc_auc_score, confusion_matrix
from imblearn.over_sampling import SMOTE
from imblearn.combine import SMOTEENN
from imblearn.pipeline import Pipeline

X_train , X_test , y_train y_test 矩阵,我成功地执行了sklearn RandomizedSearch,如下所示:

seed = 1706
knn = 10
smoted = SMOTE(sampling_strategy = 'auto',
               k_neighbors = knn,
               random_state = seed) 
mydata = pd.read_csv(datapath)
params_rf = {
  'rf__max_depth':[8, 14, 20, 26],
  'rf__min_samples_leaf':[8, 15, 22, 29],
  'rf__max_features':[6, 12, 18, 24, 30],
  'rf__n_estimators':[400, 800]
  }

smote_enn = SMOTEENN(smote = smoted)

rf = RandomForestClassifier(criterion = 'gini')

pipeline = Pipeline([('smote_enn', smote_enn), ('rf', rf)]) #<-pipeline with smote and model steps

random.seed(1706)
grid_rf = RandomizedSearchCV(estimator = pipeline,
                             param_distributions = params_rf,
                             scoring = 'roc_auc',
                             cv = 8,
                             n_jobs = cpu_count()-2,
                             refit = True,
                             return_train_score = False,
                             n_iter = 80)
grid_rf.fit(X_train, y_train.values.ravel())

from dask_ml.model_selection import RandomizedSearchCV as DaskRandomGridSearchCV
grid_rf = DaskRandomGridSearchCV(estimator = pipeline,
                                 param_distributions = params_rf,
                                 scoring = 'roc_auc',
                                 cv = 8,
                              ###n_jobs = cpu_count()-2, <-not needed b/c of dask
                                 refit = True,
                                 return_train_score = False,
                                 n_iter = 80)
grid_rf.fit(X_train, y_train.values.ravel())
AttributeError: 'SMOTEENN' object has no attribute 'transform'

为什么它与sklearn的RandomizedSearchCV一起工作,而与dask的不工作 RandomizedSearchCV

我将所有库升级到它们的最新版本。我使用的是Python3.6.9(我还在另一台运行Python3.7.3的机器上进行了尝试,并得到了相同的错误)。