diff options
Diffstat (limited to 'test/test-sets/ref/0002c.stderr')
-rw-r--r-- | test/test-sets/ref/0002c.stderr | 36 |
1 files changed, 18 insertions, 18 deletions
diff --git a/test/test-sets/ref/0002c.stderr b/test/test-sets/ref/0002c.stderr index 1c92222e..73d023e3 100644 --- a/test/test-sets/ref/0002c.stderr +++ b/test/test-sets/ref/0002c.stderr @@ -9,30 +9,30 @@ Reading datafile = train-sets/0002.dat num sources = 1 average since example example current current current loss last counter weight label predict features -0.000467 0.000467 1 1.0 0.5211 0.4995 15 -0.002842 0.005217 2 2.0 0.5353 0.4630 15 -0.007702 0.012562 4 4.0 0.5854 0.4406 15 -0.028785 0.049867 8 8.0 0.5575 0.4416 15 -0.032253 0.035720 16 16.0 0.5878 0.4855 15 -0.034047 0.035842 32 32.0 0.6038 0.4583 15 -0.024334 0.014621 64 64.0 0.5683 0.5708 15 -0.023282 0.022231 128 128.0 0.5351 0.5344 15 -0.019781 0.016280 256 256.0 0.5385 0.4886 15 -0.015457 0.011133 512 512.0 0.5053 0.4525 15 -0.014354 0.013251 1024 1024.0 0.5750 0.5073 15 -0.012754 0.011154 2048 2048.0 0.5204 0.5022 15 -0.010477 0.008200 4096 4096.0 0.5042 0.4602 15 -0.009534 0.008590 8192 8192.0 0.4967 0.4661 15 -0.008238 0.006943 16384 16384.0 0.5011 0.5376 15 -0.009146 0.010054 32768 32768.0 0.3915 0.5790 15 -0.011080 0.013014 65536 65536.0 0.5043 0.4497 15 +0.000464 0.000464 1 1.0 0.5211 0.4996 15 +0.002814 0.005164 2 2.0 0.5353 0.4634 15 +0.007663 0.012511 4 4.0 0.5854 0.4407 15 +0.028496 0.049329 8 8.0 0.5575 0.4417 15 +0.032121 0.035746 16 16.0 0.5878 0.4856 15 +0.033784 0.035448 32 32.0 0.6038 0.4587 15 +0.024142 0.014499 64 64.0 0.5683 0.5709 15 +0.023094 0.022045 128 128.0 0.5351 0.5345 15 +0.019620 0.016147 256 256.0 0.5385 0.4893 15 +0.015332 0.011044 512 512.0 0.5053 0.4533 15 +0.014235 0.013139 1024 1024.0 0.5750 0.5082 15 +0.012660 0.011085 2048 2048.0 0.5204 0.5024 15 +0.010422 0.008184 4096 4096.0 0.5042 0.4605 15 +0.009502 0.008583 8192 8192.0 0.4967 0.4662 15 +0.008239 0.006975 16384 16384.0 0.5011 0.5380 15 +0.009165 0.010091 32768 32768.0 0.3915 0.5794 15 +0.011114 0.013062 65536 65536.0 0.5043 0.4496 15 finished run number of examples per pass = 74746 passes used = 1 weighted example sum = 69521 weighted label sum = 35113.3 -average loss = 0.0106127 +average loss = 0.0106413 best constant = 0.505067 best constant's loss = 0.249974 total feature number = 1119986 |