#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on July, 2020
@author: Nathan de Lara <ndelara@enst.fr>
"""
import numpy as np
[docs]def accuracy_score(y_true: np.ndarray, y_pred: np.ndarray) -> float:
"""Accuracy: number of correctly labeled samples over total number of elements.
In the case of binary classification, this is
:math:`P = \\dfrac{TP + TN}{TP + TN + FP + FN}`.
Parameters
----------
y_true : np.ndarray
True labels.
y_pred : np.ndarray
Predicted labels
Returns
-------
precision : float
A score between 0 and 1.
Examples
--------
>>> import numpy as np
>>> y_true = np.array([0, 0, 1, 1])
>>> y_pred = np.array([0, 0, 0, 1])
>>> accuracy_score(y_true, y_pred)
0.75
"""
return (y_true == y_pred).mean()