def test_slope_one():
slpone = pyreclab.SlopeOne(dataset='dataset/u1.base',
dlmchar=b'\t',
header=False,
usercol=0,
itemcol=1,
ratingcol=2)
slpone.train()
pred = slpone.predict('457', '443')
assert abs(pred - expected_prediction) < prediction_epsilon
ranking = slpone.recommend('457', 5, includeRated=False)
assert ranking == expected_ranking
predlist, mae, rmse = slpone.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():
slpone = pyreclab.SlopeOne( dataset = 'dataset/u1.base',
dlmchar = b'\t',
header = False,
usercol = 0,
itemcol = 1,
ratingcol = 2 )
print( '-> training model' )
start = time.clock()
slpone.train()
end = time.clock()
print( 'training time: ' + str( end - start ) )
print( '-> individual test' )
pred = slpone.predict( '457', '443' )
print( 'user 457, item 443, prediction ' + str( pred ) )
ranking = slpone.recommend( '457', 5, includeRated = False )
print( 'recommendation for user 457: ' + str( ranking ) )
print( '-> prediction test' )
start = time.clock()
predlist, mae, rmse = slpone.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 = slpone.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__':
slpone = pyreclab.SlopeOne( dataset = 'dataset/u1.base',
dlmchar = b'\t',
header = False,
usercol = 0,
itemcol = 1,
ratingcol = 2 )
print( '-> training model' )
start = time.clock()
slpone.train( progress = True )
end = time.clock()
print( 'training time: ' + str( end - start ) )
print( '-> individual test' )
pred = slpone.predict( '457', '443' )
print( 'user 457, item 443, prediction ' + str( pred ) )
ranking = slpone.recommend( '457', 5, includeRated = False )
print( 'recommendation for user 457: ' + str( ranking ) )
print( '-> prediction test' )
start = time.clock()
predlist, mae, rmse = slpone.test( input_file = 'dataset/u1.test',
dlmchar = b'\t',
header = False,
usercol = 0,