only testing
Num weight bits = 16
learning rate = 10
initial_t = 1
power_t = 0.5
predictions = 0022.predict.tmp
using no cache
Reading datafile = train-sets/3parity
num sources = 1
average    since         example     example  current  current  current
loss       last          counter      weight    label  predict features
0.000000   0.000000            1         1.0  -1.0000  -1.0000        4
0.000000   0.000000            2         2.0  -1.0000  -1.0000        4
0.000000   0.000000            4         4.0  -1.0000  -1.0000        4
0.000000   0.000000            8         8.0   1.0000   1.0000        4

finished run
number of examples per pass = 8
passes used = 1
weighted example sum = 8
weighted label sum = 0
average loss = 0
best constant = -0.142857
total feature number = 32