"""Lesson 19 starter: multiclass prediction with np.argmax."""
import numpy as np

scores = np.array([
    [2.0, 1.0, 0.0],
    [0.2, 1.5, 1.1],
    [0.5, 0.5, 2.0],
    [3.0, 3.0, 1.0]
])

# np.argmax returns 0-based column indices.
zero_based = np.argmax(scores, axis=1)

# Convert to the mathematical class labels 1,2,3.
classes = zero_based + 1

print("0-based argmax indices =", zero_based)
print("class labels =", classes)

# TODO: explain what np.argmax does when two entries tie for the maximum.