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

2 votes235 views2 answers
Python sort file names with numbers
Python
-1 vote192 views2 answers
Find common values in different dataframes pandas
Python
4 votes198 views1 answer
Import discord python
Python
0 vote200 views1 answer
How to take out every even number from a list in python
Python
0 vote174 views1 answer
Faire n fois la division d'un nombre python
Python
0 vote219 views1 answer
Discord.py cog classes
Python
5 votes238 views2 answers
Django form password field
Python Django
0 vote243 views1 answer
Javascript parse url with values and anchors
Python
-1 vote269 views1 answer
Python code variable declaration
Python
0 vote212 views1 answer
Work day prior to date python
Python