creating quadratic features for pairs: ui 
only testing
Num weight bits = 16
learning rate = 10
initial_t = 1
power_t = 0.5
using no cache
Reading datafile = test-sets/ml100k_small_test
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features
2.491066 2.491066            1            1.0   5.0000   3.4217       23
2.698820 2.906574            2            2.0   5.0000   3.2951       23
2.381092 2.063364            4            4.0   4.0000   3.2078       23
1.469532 0.557971            8            8.0   4.0000   3.2111       23
1.509373 1.549214           16           16.0   5.0000   3.2134       23

finished run
number of examples = 30
weighted example sum = 30.000000
weighted label sum = 110.000000
average loss = 1.457823
best constant = 3.666667
total feature number = 690
