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only testing
Num weight bits = 18
learning rate = 10
initial_t = 1
power_t = 0.5
predictions = sequence_data.predict
using no cache
Reading datafile = train-sets/sequence_data
num sources = 1
average since example example current current current
loss last counter weight label predict features
average since sequence example current label current predicted current cur cur predic. examples
loss last counter weight sequence prefix sequence prefix features pass pol made gener.
0.000000 0.000000 1 1.000000 [5 4 3 2 1 ] [5 4 3 2 1 ] 15 0 0 5 0
finished run
number of examples per pass = 1
passes used = 1
weighted example sum = 1
weighted label sum = 0
average loss = 0
best constant = -inf
total feature number = 15
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