# accuracy_score

### cuml.metrics.accuracy_score(y_true, y_pred, , sample_weight=None, normalize=True)[[source]](https://github.com/NVIDIA/cuml/blob/93418baf5/python/cuml/cuml/metrics/_classification.py#L54)

Accuracy classification score.

* **Parameters:**
  **y_true**
  : Ground truth (correct) labels.

  **y_pred**
  : Predicted labels.

  **sample_weight**
  : Sample weights.

  **normalize**
  : If `False`, return the number of correctly classified samples.
    Otherwise, return the fraction of correctly classified samples.
* **Returns:**
  **score**
  : The fraction of correctly classified samples, or the number of correctly
    classified samples if `normalize == False`.

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