predictions = 0098.predict
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/0001.dat
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features
0.159321 0.095132          256          256.0   0.0000   0.2566       71

finished run
number of examples per pass = 200
passes used = 2
weighted example sum = 400.000000
weighted label sum = 182.000000
average loss = 0.104047
best constant = 0.455000
best constant's loss = 0.247975
total feature number = 30964
