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

7 votes140 views1 answer
Python html to pdf
Python
7 votes149 views2 answers
Create the dataframe column based on condition
Python
17 votes92 views3 answers
Get last row of dataframe
Python
2 votes134 views1 answer
Python force string parameter
Python
-2 votes138 views1 answer
Python: raise error
Python
2 votes122 views1 answer
Directory name python
Python
78 votes131 views6 answers
Python check version
Python
4 votes164 views1 answer
When was python developed
Python
0 vote83 views2 answers
Python fraction simplify
Python
0 vote130 views1 answer
How to move the element of an array in python by one step
Python