ScikitLearners.py 文件源码

def calculateMetrics(truth, predicted):
    """
    Calculates and returns a set of metrics from ground truth and predicted vectors
    :param truth: A list of ground truth labels
    :type truth: list
    :param predicted: A list of predicted labels
    :type predicted: list
    :return: A dict of metrics including accuracy, recall, specificity, precision, and F1-score
    """
    try:
        # Sanity check
        if not len(truth) == len(predicted):
            prettyPrint("The two vectors have different dimensionality", "warning")
            return {}

        metrics = {}
        # Calculate different mterics
        metrics["accuracy"] = accuracy_score(truth, predicted)
        metrics["recall"] = recall_score(truth, predicted)
        metrics["specificity"] = specificity_score(truth, predicted) # From Aion.utils.misc
        metrics["precision"] = precision_score(truth, predicted)
        metrics["f1score"] = f1_score(truth, predicted)

    except Exception as e:
        prettyPrintError(e)
        return {}

    return metrics