"""Brier Loss"""
import typing
import numpy as np
from h2oaicore.metrics import CustomScorer
from sklearn.metrics import brier_score_loss
from sklearn.preprocessing import LabelEncoder
class MyBrierLoss(CustomScorer):
_description = "Brier Score Loss"
_binary = True
_maximize = False
_perfect_score = 0
_display_name = "BRIER"
def score(self,
actual: np.array,
predicted: np.array,
sample_weight: typing.Optional[np.array] = None,
labels: typing.Optional[np.array] = None,
**kwargs) -> float:
lb = LabelEncoder()
labels = lb.fit_transform(labels)
actual = lb.transform(actual)
return brier_score_loss(actual, predicted, sample_weight, pos_label=labels[1])
