def test_item_avg():
iavg = pyreclab.ItemAvg(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
iavg.train()
pred = iavg.predict('457', '443')
assert abs(pred - expected_prediction) < prediction_epsilon
ranking = iavg.recommend('457', 5, includeRated=False)
assert ranking == expected_ranking
predlist, mae, rmse = iavg.test(input_file='dataset/u1.test',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2,
output_file='predictions.csv')
assert abs(mae - expected_mae) < mae_epsilon
assert abs(rmse - expected_rmse) < rmse_epsilon
def main():
iavg = pyreclab.ItemAvg(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
print('-> training model')
start = time.clock()
iavg.train()
end = time.clock()
print('training time: ' + str(end - start))
print('-> individual test')
pred = iavg.predict('457', '443')
print('user 457, item 443, prediction ' + str(pred))
ranking = iavg.recommend('457', 5, includeRated=False)
print('recommendation for user 457: ' + str(ranking))
print('-> prediction test')
start = time.clock()
predlist, mae, rmse = iavg.test(input_file='dataset/u1.test',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2,
output_file='predictions.csv')
end = time.clock()
print('prediction time: ' + str(end - start))
print('MAE: ' + str(mae))
print('RMSE: ' + str(rmse))
print('-> recommendation test')
start = time.clock()
recommendList = iavg.testrec(input_file='dataset/u1.test',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2,
topn=10,
output_file='ranking.json',
includeRated=False)
end = time.clock()
print('recommendation time: ' + str(end - start))
import time
import pyreclab
if __name__ == '__main__':
iavg = pyreclab.ItemAvg(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
print('-> training model')
start = time.clock()
iavg.train()
end = time.clock()
print('training time: ' + str(end - start))
print('-> individual test')
pred = iavg.predict('457', '443')
print('user 457, item 443, prediction ' + str(pred))
ranking = iavg.recommend('457', 5, includeRated=False)
print('recommendation for user 457: ' + str(ranking))
print('-> prediction test')
start = time.clock()
predlist, mae, rmse = iavg.test(input_file='dataset/u1.test',
dlmchar=b'\t',
header=False,
usercol=0,