/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

0 vote119 views1 answer
Using shebang python
Python
0 vote88 views1 answer
Logout redirect url
Python
2 votes126 views2 answers
Numpy rolling average
Python
0 vote115 views1 answer
Python string: .replace()
Python
0 vote138 views1 answer
Django request.data example
Python Django
5 votes106 views1 answer
Difference between list vs set vs map in java
Python
0 vote113 views1 answer
Count proportion pandas
Python
1 vote121 views1 answer
Lru cache python
Python
6 votes111 views1 answer
Python sort
Python
14 votes125 views6 answers
Binary search in python
Python