deeppavlov/metrics/accuracy.py
def round_accuracy(y_true, y_predicted):
    """
    Rounds predictions and calculates accuracy in terms of absolute coincidence.

    Args:
        y_true: list of true values
        y_predicted: list of predicted values

    Returns:
        portion of absolutely coincidental samples
    """
    predictions = [round(x) for x in y_predicted]
    examples_len = len(y_true)
    correct = sum([y1 == y2 for y1, y2 in zip(y_true, predictions)])
    return correct / examples_len if examples_len else 0
def round_accuracy(y_true, y_predicted):
    predictions = [round(x) for x in y_predicted]
    examples_len = len(y_true)
    correct = sum([y1 == y2 for y1, y2 in zip(y_true, predictions)])
    return correct / examples_len if examples_len else 0
def round_accuracy ( y_true , y_predicted ) : predictions = [ round ( x ) for x in y_predicted ] examples_len = len ( y_true ) correct = sum ( [ y1 == y2 for y1 , y2 in zip ( y_true , predictions ) ] ) return correct / examples_len if examples_len else 0
Rounds predictions and calculates accuracy in terms of absolute coincidence.

    Args:
        y_true: list of true values
        y_predicted: list of predicted values

    Returns:
        portion of absolutely coincidental samples
Rounds predictions and calculates accuracy in terms of absolute coincidence .