Created
June 7, 2012 19:23
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Calculates the Mean Average Precision, as in: http://www.kaggle.com/c/FacebookRecruiting/details/Evaluation
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#!/usr/bin/env python | |
import sys | |
import csv | |
def MeanAveragePrecision(valid_filename, attempt_filename, at=10): | |
at = int(at) | |
valid = dict() | |
for line in csv.DictReader(open(valid_filename,'r')): | |
valid.setdefault(line['source_node'],set()).update(line['destination_nodes'].split(" ")) | |
attempt = list() | |
for line in csv.DictReader(open(attempt_filename,'r')): | |
attempt.append([line['source_node'], line['destination_nodes'].split(" ")]) | |
average_precisions = list() | |
for entry in attempt: | |
node = entry[0] | |
predictions = entry[1] | |
correct = list(valid.get(node,dict())) | |
total_correct = len(correct) | |
if len(predictions) == 0 or total_correct == 0: | |
average_precisions.append(0) | |
continue | |
running_correct_count = 0 | |
running_score = 0 | |
for i in range(min(len(predictions),at)): | |
if predictions[i] in correct: | |
correct.remove(predictions[i]) | |
running_correct_count += 1 | |
running_score += float(running_correct_count) / (i+1) | |
average_precisions.append(running_score / min(total_correct, at)) | |
return sum(average_precisions) / len(average_precisions) | |
if __name__ == "__main__": | |
if len(sys.argv) == 3: | |
print MeanAveragePrecision(sys.argv[1], sys.argv[2]) | |
elif len(sys.argv) == 4: | |
print MeanAveragePrecision(sys.argv[1], sys.argv[2], sys.argv[3]) | |
else: | |
print "args: valid.csv attempt.csv [10]" |
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