Find a labels mapper with the highest accuracy.

permutation_accuracy.py

from itertools import permutations

import numpy as np
from sklearn.metrics import accuracy_score

np.random.seed(42)

y_true = np.random.randint(low=0, high=3, size=100)

noize_mapper = {0: 1, 1: 2, 2: 0}
y_pred = np.array([noize_mapper[label] for label in y_true])

for labels in permutations(set(y_pred)):
    mapper = {i: label for i, label in enumerate(labels)}
    y_pred_new = np.array([mapper[label] for label in y_pred])

    accuracy = accuracy_score(
        y_true=y_true,
        y_pred=y_pred_new,
    )

    print(f"mapper: {mapper}\naccuracy: {accuracy}\n")