only testing
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/marginal_features
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features
0.000000 0.000000            1            1.0   0.5000   0.5006        4
0.000004 0.000008            2            2.0   1.0000   0.9972        4
0.000004 0.000004            4            4.0   0.5000   0.5010        4

finished run
number of examples = 4
weighted example sum = 4.000000
weighted label sum = 2.250000
average loss = 0.000004
best constant = 0.562500
total feature number = 16
