#0156

Check Stratified Split Counts

MediumML25 min20 XP

Problem

Given train labels and test labels, return a dictionary containing class counts for each split.

Why This Matters

A split can silently break evaluation if rare classes disappear from train or test.

Function Signature

def split_class_counts(y_train, y_test):

Examples

Example 1

Inputy_train = [0,0,1,1,1], y_test = [0,1]

Output{'train': {0: 2, 1: 3}, 'test': {0: 1, 1: 1}}

Both splits contain both classes, but proportions differ.

Constraints

Return the exact requested value.
Handle empty or small inputs when the prompt allows them.
Keep the code readable and deterministic.

CodePython

def split_class_counts(y_train, y_test):
    """
    Input example: y_train = [0,0,1,1,1], y_test = [0,1]
    Return: {'train': {0: 2, 1: 3}, 'test': {0: 1, 1: 1}}
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return {}

def split_class_counts(y_train, y_test):
    """
    Input example: y_train = [0,0,1,1,1], y_test = [0,1]
    Return: {'train': {0: 2, 1: 3}, 'test': {0: 1, 1: 1}}
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return {}

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Inputy_train = [0,0,1,1,1], y_test = [0,1]

Expected{'train': {0: 2, 1: 3}, 'test': {0: 1, 1: 1}}

Both splits contain both classes, but proportions differ.

Hidden Test Categories

empty or smallest inputduplicates or repeated valueslarger realistic input