/Python/From sklearn.metrics import classification_report

From sklearn.metrics import classification_report

Classification report scikit

from sklearn.metrics import classification_report

target_names = ['first_value_y','second_value_y'] # target values

# Print classification report after a train/test split:
print(classification_report(y_test, y_pred, target_names=target_names))

From sklearn.metrics import classification_report

>>> from sklearn.metrics import classification_report
>>> y_true = [0, 1, 2, 2, 2]
>>> y_pred = [0, 0, 2, 2, 1]
>>> target_names = ['class 0', 'class 1', 'class 2']
>>> print(classification_report(y_true, y_pred, target_names=target_names))
             precision    recall  f1-score   support

    class 0       0.50      1.00      0.67         1
    class 1       0.00      0.00      0.00         1
    class 2       1.00      0.67      0.80         3

avg / total       0.70      0.60      0.61         5

Source: scikit-learn.org

Similar codes

8 votes280 views1 answer
Negative lookbehind javascript
Python
2 votes303 views2 answers
Python version kali linux
Python
0 vote324 views1 answer
How to make a script that reads from Database and then writes to the csv file and then uploads the file to Google Drive in python
Python
1 vote314 views1 answer
Install serial python
Python
0 vote314 views1 answer
Python replace \n with something else
Python
0 vote309 views2 answers
Python open google
Python
0 vote316 views1 answer
Python use negation with maskedarray
Python
1 vote296 views1 answer
Ffmpeg python video from images
Python
22 votes300 views4 answers
Palindrome checker python
Python
9 votes282 views4 answers
Pandas count number of rows with value
Python