def test_most_popular():
mpop = pyreclab.MostPopular(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
mpop.train(5)
ranking = mpop.recommend('457', 5, includeRated=False)
assert ranking == expected_ranking
import time
import pyreclab
if __name__ == '__main__':
model = pyreclab.MostPopular(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
print('-> training model')
start = time.clock()
model.train(5, progress=True)
end = time.clock()
print('training time: ' + str(end - start))
print('-> individual test')
ranking = model.recommend('457', 5, includeRated=False)
print('user 457, recommended items ' + str(ranking))
print('-> recommendation test')
start = time.clock()
recommendList, maprec, ndcg = model.testrec(input_file='dataset/u1.test',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2,
topn=10,
