#Three lines to make our compiler able to draw:
import sys
import matplotlib
matplotlib.use('Agg')
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score, confusion_matrix, roc_auc_score, roc_curve
n = 10000
y = np.array([0] * n + [1] * n)
#
y_prob_1 = np.array(
np.random.uniform(.25, .5, n//2).tolist() +
np.random.uniform(.3, .7, n).tolist() +
np.random.uniform(.5, .75, n//2).tolist()
)
y_prob_2 = np.array(
np.random.uniform(0, .4, n//2).tolist() +
np.random.uniform(.3, .7, n).tolist() +
np.random.uniform(.6, 1, n//2).tolist()
)
def plot_roc_curve(true_y, y_prob):
"""
plots the roc curve based of the probabilities
