"""
Copyright 2018 Johns Hopkins University (Author: Jesus Villalba)
Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""
import numpy as np
from sklearn.metrics import accuracy_score
[docs]def compute_accuracy(y_true, y_pred, normalize=True, sample_weight=None):
"""Computes accuracy
Args:
y_true: 1d array-like, or label indicator array / sparse matrix.
Ground truth (correct) labels.
y_pred: 1d array-like, or label indicator array / sparse matrix.
Predicted labels, as returned by a classifier.
normalize: If False, return the number of correctly classified samples.
Otherwise, return the fraction of correctly classified samples.
sample_weight: Sample weights.
Returns:
Accuracy or number of correctly classified samples.
"""
return accuracy_score(y_true, y_pred, normalize, sample_weight)