#0135

Argmax Per Row

EasyNumPy15 min10 XP

Problem

Given a 2D NumPy array, return a 1D array of column indexes where each row is largest.

Why This Matters

Argmax over class probabilities is how many classifiers convert scores into predicted labels.

Function Signature

def argmax_rows(scores):

Examples

Example 1

Input[[0.1,0.9],[0.8,0.2]]

Output[1, 0]

First row max is column 1; second row max is column 0.

Constraints

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

CodePython

import numpy as np

def argmax_rows(scores):
    """
    Input example: [[0.1,0.9],[0.8,0.2]]
    Return: [1, 0]
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return scores

import numpy as np

def argmax_rows(scores):
    """
    Input example: [[0.1,0.9],[0.8,0.2]]
    Return: [1, 0]
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return scores

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Input[[0.1,0.9],[0.8,0.2]]

Expected[1, 0]

First row max is column 1; second row max is column 0.

Hidden Test Categories

three columnsties choose firstsingle row