access to numbers in classification_report - sklearn
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
You can output the classification report as dict with:
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']
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
You can use output_dict parameter in build-in classification_report to return a dictionary:
classification_report(y_true,y_pred,output_dict=True)