#0139

Majority Class Baseline Accuracy

EasyML15 min10 XP

Problem

Given labels, return the accuracy of a classifier that always predicts the most frequent label. Break ties by choosing any tied class.

Why This Matters

A model must beat simple baselines. Accuracy without a baseline is hard to judge.

Function Signature

def majority_baseline_accuracy(labels):

Examples

Example 1

Input[1, 1, 0, 1, 0]

Output0.6

Class 1 appears 3 of 5 times.

Constraints

Return the exact requested structure.
Handle normal edge cases cleanly.
Prefer readable code over clever shortcuts.

CodePython

def majority_baseline_accuracy(labels):
    """
    Input example: [1, 1, 0, 1, 0]
    Return: 0.6
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return 0

def majority_baseline_accuracy(labels):
    """
    Input example: [1, 1, 0, 1, 0]
    Return: 0.6
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return 0

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Input[1, 1, 0, 1, 0]

Expected0.6

Class 1 appears 3 of 5 times.

Hidden Test Categories

all same classtiestring labels