8 examples of 'accuracy sklearn' in Python

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def test_accuracy(clf, X_test, y_test):
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	X_test = np.array([item for sublist in X_test for item in sublist])
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	y_test = np.array([item for sublist in y_test for item in sublist])
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	return clf.score(X_test, y_test)

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def accuracy(params):
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    clf = RandomForestClassifier(**params)
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    clf.fit(x_train,y_train)
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    return clf.score(x_test, y_test)

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def accuracy(y_test, y_pred):
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  """Computes the accuracy score.
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  Args:
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    y_test: np.array 1-D array of true class labels
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    y_pred: np.array 1-D array of predicted class labels
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  Returns:
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    accuracy: float
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      accuracy score
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  """
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  return metrics.accuracy_score(y_test, y_pred)

26
def accuracy_score(self, x_test, y_test):
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    estimation = self.model.predict(x_test)
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    return acc_func(estimation,y_test)

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@torch.no_grad()
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def compute_accuracy_classifier(clf, data_train, labels_train, data_test, labels_test):
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    clf.fit(data_train, labels_train)
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    # Predicting the labels
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    y_pred_test = clf.predict(data_test)
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    y_pred_train = clf.predict(data_train)
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    return (
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        (
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            compute_accuracy_tuple(labels_train, y_pred_train),
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            compute_accuracy_tuple(labels_test, y_pred_test),
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        ),
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        y_pred_test,
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    )

29
def testAccuracy(data_test, label_test, kNN):
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    return kNN.score(data_test, label_test)

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def get_accuracy(self, x_test, y_test, keep_prob=1.0):
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    return self.sess.run(self.accuracy, feed_dict={self.X: x_test, self.Y: y_test, self.keep_prob: keep_prob})

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@unhot
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def accuracy(actual, predicted):
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    return 1.0 - classification_error(actual, predicted)