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

1 vote189 views1 answer
Django add to cart
Python
14 votes233 views5 answers
View all columns pandas
Python
6 votes187 views3 answers
Python console pause
Python
85 votes228 views4 answers
Create python executable
Python
0 vote190 views1 answer
Pkl save multiple files
Python
0 vote194 views1 answer
300 x 250 donut download
Python
68 votes202 views6 answers
Create directory in python
Python
8 votes187 views2 answers
Find max in a dataframe
Python
0 vote183 views1 answer
How to rename rengeindex pandas
Python
0 vote190 views1 answer
Python disable warning deprecated
Python