/Python/Cross_val_score scoring parameters types

Cross_val_score scoring parameters types

>>> from sklearn import svm, cross_validation, datasets
>>> iris = datasets.load_iris()
>>> X, y = iris.data, iris.target
>>> model = svm.SVC()
>>> cross_validation.cross_val_score(model, X, y, scoring='wrong_choice')
Traceback (most recent call last):
ValueError: 'wrong_choice' is not a valid scoring value. Valid options are ['accuracy', 'adjusted_rand_score', 'average_precision', 'f1', 'log_loss', 'mean_absolute_error', 'mean_squared_error', 'precision', 'r2', 'recall', 'roc_auc']

Source: scikit-learn.org

Similar codes

61 votes161 views6 answers
Python classes
Python
0 vote202 views1 answer
Iloc[:,0:-1]
Python
1 vote152 views1 answer
How to print x in python
Python
1 vote159 views2 answers
Correlation between categorical and continuous variables
Python
18 votes155 views6 answers
Factorial python
Python
0 vote269 views1 answer
Shared a local host django
Python Django
0 vote173 views1 answer
Print all variables jupyter notebook
Python
25 votes186 views4 answers
Time in python code
Python
0 vote162 views1 answer
Group by, aggregate multiple column -pandas
Python
7 votes170 views1 answer
Python title case
Python