majority-bag-vote — Airbnb case
Beginner
Airbnb-inspired listing-quality model uses several bootstrap-trained classifiers that may disagree on a prediction. You need to aggregate their class votes deterministically so the team has a reliable majority-vote baseline.
predictions holds the class predicted by each bootstrap-trained classifier for one sample. Return the most frequent class; if several classes tie, return the smallest.
Implement solve(predictions).
Returns. Return the winning class as a Python int. Classes are non-negative integers.
Examples
Example 1
Input:
solve([0, 1, 1, 0, 1])
Output:
1
Example 2
Input:
solve([2, 0, 2, 0, 1])
Output:
0
Keywords
problemsetclassical-ml-trees-ensemblesbaggingairbnb
Python
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