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predictions = cb_adf_dr.predict
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/cb_test.ldf
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features
2.000000 2.000000            1            1.0    known        0...       19
0.920996 -0.158008            2            2.0    known        1...        9

finished run
number of examples per pass = 3
passes used = 1
weighted example sum = 3.000000
weighted label sum = 0.000000
average loss = 0.613997
total feature number = 37