Accuracy for each class

from sklearn.metrics import confusion_matrix
import numpy as np

y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_names = ['class 0', 'class 1', 'class 2']

#Get the confusion matrix
cm = confusion_matrix(y_true, y_pred)
#array([[1, 0, 0],
#   [1, 0, 0],
#   [0, 1, 2]])

#Now the normalize the diagonal entries
cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
#array([[1.        , 0.        , 0.        ],
#      [1.        , 0.        , 0.        ],
#      [0.        , 0.33333333, 0.66666667]])

#The diagonal entries are the accuracies of each class
cm.diagonal()
#array([1.        , 0.        , 0.66666667])

Source: stackoverflow.com

Similar codes

0 vote315 views1 answer
Python str and repr
Python
1 vote304 views1 answer
Can you print to multiple output files python
Python
0 vote282 views1 answer
Unction which takes in a list of integers and returns a dictionary of the five number summary..
Python
2 votes244 views1 answer
Upper input python
Python
3 votes308 views2 answers
Rest_framework_simplejwt
Python
0 vote340 views2 answers
Split paragraphs in python
Python
11 votes346 views2 answers
Check if file is txt python
Python
4 votes336 views1 answer
Django is null
Python Django
0 vote243 views1 answer
Arabert
Python
-1 vote333 views1 answer
Python serial port
Python