access to numbers in classification_report – sklearn

Question

This is a simple example of classification_report in sklearn

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

I want to have access to avg/total row. For instance, I want to extract f1-score from the report, which is 0.61.

How can I have access to the number in classification_report?

Asked By: Hadij

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Source

Answer 1

classification_report is string so I would suggest you to use f1_score from scikit-learn

from sklearn.metrics import f1_score
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_names = ['class 0', 'class 1', 'class 2']

print(f1_score(y_true, y_pred, average=None)

output

Answered By: Sociopath

Answer 2

you can use precision_recall_fscore_support for getting all at once

from sklearn.metrics import precision_recall_fscore_support as score
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
precision,recall,fscore,support=score(y_true,y_pred,average='macro')
print 'Precision : {}'.format(precision)
print 'Recall    : {}'.format(recall)
print 'F-score   : {}'.format(fscore)
print 'Support   : {}'.format(support)

here is the link to the module

Answered By: Pratik Kumar

Answer 3

You can use output_dict parameter in build-in classification_report to return a dictionary:

classification_report(y_true,y_pred,output_dict=True)

Answered By: Gamugo

Answer 4

You can output the classification report by adding output_dict=True to the report:

report = classification_report(y_true, y_pred, output_dict=True)

And then access its single values as in a normal python dictionary.

For example, the macro metrics:

macro_precision =  report['macro avg']['precision'] 
macro_recall = report['macro avg']['recall']    
macro_f1 = report['macro avg']['f1-score']

or Accuracy:

accuracy = report['accuracy']

Answered By: Rmobdick

access to numbers in classification_report – sklearn

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