final_regressor = mwt.model
predictions = cb_eval1.preds
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/cb_eval1
num sources = 1
average  since         example        example  current  current  current
loss     last          counter         weight    label  predict features

finished run
number of examples = 4
weighted example sum = 4.000000
weighted label sum = 0.000000
average loss = 0.000000
total feature number = 12
