Num weight bits = 18
learning rate = 10
initial_t = 1
power_t = 0.5
decay_learning_rate = 1
predictions = cs_test.ldf.wap.predict
creating cache_file = train-sets/cs_test.ldf.cache
Reading datafile = train-sets/cs_test.ldf
num sources = 1
average    since         example     example  current  current  current
loss       last          counter      weight    label  predict features
1.000000   1.000000          1      1.0    known        1        3
0.500000   0.000000          2      2.0    known        0        3
0.500000   0.500000          4      4.0    known        0        3
0.375000   0.250000          8      8.0    known        0        3
0.375000   0.375000         16     16.0    known        0        3

finished run
number of examples per pass = 3
passes used = 10
weighted example sum = 30
weighted label sum = 0
average loss = 0.366667
best constant = -0.0344828
total feature number = 210