#0138

Min-Max Scale Train and Test

MediumML25 min20 XP

Problem

Given train and test lists, scale both using train min and train max. If train range is zero, use range 1.

Why This Matters

This reinforces one of the most important ML habits: never fit preprocessing on test data.

Function Signature

def minmax_train_test(train, test):

Examples

Example 1

Inputtrain=[10,20,30], test=[40]

Outputtrain=[0,0.5,1], test=[1.5]

The test value is scaled using train min 10 and max 30.

Constraints

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

CodePython

def minmax_train_test(train, test):
    """
    Input example: train=[10,20,30], test=[40]
    Return: train=[0,0.5,1], test=[1.5]
    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 minmax_train_test(train, test):
    """
    Input example: train=[10,20,30], test=[40]
    Return: train=[0,0.5,1], test=[1.5]
    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

Inputtrain=[10,20,30], test=[40]

Expectedtrain=[0,0.5,1], test=[1.5]

The test value is scaled using train min 10 and max 30.

Hidden Test Categories

constant trainnegative valuestest below train min