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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
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