Course: Data Science - Classification - Binary Disorder

Question

Explanation: "...Of the two false labels, both were correctly predicted; that is, zero false positive and two true negatives..."

Shouldn't it be "...Of the two false labels, both were correctly predicted; that is, zero false NEGATIVE and two true negatives..."

Answer 1

y_true = [int(x) for x in input().split()]
y_pred = [int(x) for x in input().split()]

from sklearn.metrics import confusion_matrix
import numpy as np

cm = confusion_matrix(y_pred, y_true, labels=[1,0])

print(np.array(cm, dtype='f'))

Answer 2

here we have to use y_pred first in confusion matrix then y_true to get the result

confusion_matrix( y_pred_arr,y_true_arr, labels=[1,0])

Answer 3

Please copy my answer and like check

Answer 4

from sklearn.metrics import confusion_matrix

y_true = [int(x) for x in input().split()]
y_pred = [int(x) for x in input().split()]

m = confusion_matrix(y_pred,y_true, labels = [1,0])

print(m.astype(float))