CODEWITHSUNDEEP
pythonfunctionmachine-learningscikit-learncross-validation
alvas
alvas

Reputation: 122260

Where is the score function in scikit-learn classifiers located?

When running cross-validation within scikit-learn, all classifiers would have a factory function score() which I can easily check the accuracy of the classifier, e.g. from http://scikit-learn.org/stable/modules/cross_validation.html

>>> import numpy as np
>>> from sklearn import cross_validation
>>> from sklearn import datasets
>>> from sklearn import svm

>>> iris = datasets.load_iris()
>>> iris.data.shape, iris.target.shape
((150, 4), (150,))
>>> X_train, X_test, y_train, y_test = cross_validation.train_test_split(
...     iris.data, iris.target, test_size=0.4, random_state=0)

>>> X_train.shape, y_train.shape
((90, 4), (90,))
>>> X_test.shape, y_test.shape
((60, 4), (60,))

>>> clf = svm.SVC(kernel='linear', C=1).fit(X_train, y_train)
>>> clf.score(X_test, y_test)                           
0.96...

After digging into the github repo for scikit-learn, I still can't figure out where is the function for the clf.score() function.

There is this link but it doesn't contain the score(), https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/svm/classes.py

Where is the score() function for sklearn classifiers located?

I could implement my own score function easily, but the aim is to build my library so that it is coherent with the sklearn classifiers, not to come up with my own scoring function =)

Upvotes: 1

Views: 2447

Answers (1)

jakevdp
jakevdp

Reputation: 86473

The default score() method for scikit-learn classifiers is the accuracy score, and is defined in the ClassifierMixin class. This mixin is a parent class of most (all?) of scikit-learn's built-in classifiers.

If you're writing your own classifier, I would suggest inheriting from this mixin and BaseEstimator as well, so that you'll get the scoring and other features for your model automatically.

Upvotes: 7

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