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 vote307 views1 answer
Making gifs via python
Python
6 votes350 views2 answers
Scatter plot plotly
Python
1 vote313 views1 answer
Plot value counta
Python
0 vote299 views1 answer
Legend text color matplotlib
Python
1 vote354 views2 answers
How to uninstall python2.7 from ubuntu 18.04
Python
35 votes318 views2 answers
How to run cmd line commands in python
Python
0 vote333 views1 answer
Serializer phonenumber field json
Python
0 vote338 views1 answer
ImportError: cannot import name 'clock' from 'time' (unknown location)
Python
1 vote321 views1 answer
Python how much memory does a variable need
Python
1 vote317 views3 answers
How to get today weekday in python
Python