How to count the number of times 1s predicted by a classifier for a particular instance-CodePudding

Suppose I have a following lists of list containing labels predicted by a 3 classifier of same type

List = [[0,1,1,0],[1,1,1,0],[0,0,1,1]]

How can I get the following?

List1 =[0,1,1,0]

which are labels that are predicted by most of the classifiers.

CodePudding user response：

zip the lists together and get the most common element from each tuple.

arr = [[0, 1, 1, 0], [1, 1, 1, 0], [0, 0, 1, 1]]
[max(set(x), key=x.count) for x in zip(*arr)]
# [0, 1, 1, 0]

Or, using pandas, convert the list of lists to a DataFrame and get mode along the columns

import pandas as pd

pd.DataFrame(arr).mode().iloc[0,:].tolist()
# [0, 1, 1, 0]