Calculate Accuracy Score

Problem

Calculate the accuracy score of predictions compared to true labels. Given two arrays (true labels and predicted labels), return the fraction of correct predictions.

Solution

import numpy as np

def accuracy_score(y_true, y_pred):
    y_true = np.array(y_true)
    y_pred = np.array(y_pred)
    correct = np.sum(y_true == y_pred)
    return correct / len(y_true)

Explanation

1. Convert inputs to NumPy arrays for element-wise comparison.
2. Compare predicted labels to true labels element-wise, producing a boolean array.
3. Sum the True values (correct predictions).
4. Divide by the total number of samples to get the accuracy ratio.

Complexity

• Time: O(n) where n is the number of samples
• Space: O(n) for the boolean comparison array