CODEWITHSUNDEEP
pythonmachine-learningscikit-learnmultilabel-classification
RJFF
RJFF

Reputation: 37

How calculate prediction accuracy of OneVsRestClassifier?

how I can calculate the prediction Accuracy and F1 Score of OneVsRestClassifier?

>>> from sklearn import datasets
>>> from sklearn.multiclass import OneVsRestClassifier
>>> from sklearn.svm import LinearSVC
>>> iris = datasets.load_iris()
>>> X, y = iris.data, iris.target
>>> OneVsRestClassifier(LinearSVC(random_state=0)).fit(X, y).predict(X)

Upvotes: 0

Views: 1090

Answers (1)

Kyle
Kyle

Reputation: 467

You can use sklearn's metrics module.

from sklearn import datasets
from sklearn.multiclass import OneVsRestClassifier
from sklearn.svm import LinearSVC
from sklearn.metrics import accuracy_score, f1_score

iris = datasets.load_iris()
X, y = iris.data, iris.target
model = OneVsRestClassifier(LinearSVC(random_state=0))
model.fit(X, y)
yhat = model.predict(X)

print('Accuracy:', accuracy_score(y, yhat))
print('F1:', f1_score(y, yhat, average='micro'))

Note that I set the average argument to micro. You can change this based on the options here.

Upvotes: 2

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