metrics.py

# via https://github.com/benhamner/Metrics/blob/master/Python/ml_metrics/average_precision.py
# Copyright (c) 2012, Ben Hamner (ben@benhamner.com)
def apk(actual, predicted, k=10):
    """
    Computes the average precision at k.
    This function computes the average prescision at k between two lists of
    items.
    Parameters
    ----------
    actual : list
             A list of elements that are to be predicted (order doesn't matter)
    predicted : list
                A list of predicted elements (order does matter)
    k : int, optional
        The maximum number of predicted elements
    Returns
    -------
    score : double
            The average precision at k over the input lists
    """
    if actual is None or len(actual) == 0:
        return 0.0

    if predicted is None or len(predicted) == 0:
        return 0.0

    if len(predicted)>k:
        predicted = predicted[:k]

    score = 0.0
    num_hits = 0.0

    for i,p in enumerate(predicted):
        if p in actual and p not in predicted[:i]:
            num_hits += 1.0
            score += num_hits / (i+1.0)

    return score / min(len(actual), k)