Majority vote: argmax, bincount, average

Weighted majority vote

import numpy as np

np.argmax(np.bincount([0, 0, 1], weights=[0.2, 0.2, 0.6]))

1

Weighted majority vote based on class probabilities

Assuming a binary classifier $i \in {0,1}$ and an ensemble of three classifiers $C_j \left(j \in {1,2,3} \right)$

prob_output = np.array([[0.9, 0.1],
               [0.8, 0.2],
               [0.4, 0.6]])

# p(i_0|x) = 0.2x0.9 + 0.2x0.8 + 0.6x0.4 = 0.58
p = np.average(prob_output, 
               axis=0, 
               weights=[0.2, 0.2, 0.6])
p

array([0.58, 0.42])

np.argmax(p)

0