only testing
predictions = poisson.preds
Num weight bits = 2
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/poisson.dat
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features
97.853516 97.853516            1            1.0  12.0000   8.2310        3
83.212708 68.571899            2            2.0  11.0000  15.1679        3
71.244273 59.275838            4            4.0  13.0000   9.3978        3
67.120024 62.995776            8            8.0  14.0000   9.5008        3
74.782126 82.444227           16           16.0   9.0000   4.7840        3
55.771219 36.760312           32           32.0   6.0000   7.1309        3
72.710577 89.649934           64           64.0   6.0000   5.7325        3

finished run
number of examples per pass = 100
passes used = 1
weighted example sum = 100.000000
weighted label sum = 916.000000
average loss = 75.217167
best constant = 9.160000
total feature number = 276
