cross val score scoring parameters types

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Simon
03 May 2020
1>>> from sklearn import svm, cross_validation, datasets
2>>> iris = datasets.load_iris()
3>>> X, y = iris.data, iris.target
4>>> model = svm.SVC()
5>>> cross_validation.cross_val_score(model, X, y, scoring='wrong_choice')
6Traceback (most recent call last):
7ValueError: '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']
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