from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier as RFC
from sklearn.neighbors import KNeighborsClassifier as KNC
from sklearn.ensemble import VotingClassifier as VC
import numpy as np

X, y = load_iris(return_X_y=True)
models=[('knc', KNC()),('rnc', KNC())]
weights=np.array((1,2))
vc = VC(estimators=models, weights=weights)
vc.fit(X,y)

ValueError                                Traceback (most recent call last)
<ipython-input-6-cc5618b5c2ae> in <module>()
      9 weights=np.array((1,2))
     10 vc = VC(estimators=models, weights=weights)
---> 11 vc.fit(X,y)


    142                                  ' tuples')
    143 
--> 144         if self.weights and len(self.weights) != len(self.estimators):
    145             raise ValueError('Number of classifiers and weights must be equal'
    146                              '; got %d weights, %d estimators'

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()