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Diffstat (limited to 'test/train-sets/ref/0002a.stderr')
-rw-r--r--test/train-sets/ref/0002a.stderr30
1 files changed, 15 insertions, 15 deletions
diff --git a/test/train-sets/ref/0002a.stderr b/test/train-sets/ref/0002a.stderr
index 2fc2b9a2..8f3de1e9 100644
--- a/test/train-sets/ref/0002a.stderr
+++ b/test/train-sets/ref/0002a.stderr
@@ -10,27 +10,27 @@ power_t = 0
learning_rate set to 10
average since example example current current current
loss last counter weight label predict features
-0.146972 0.146972 3 3.0 0.5498 0.2139 197
-0.088641 0.030310 6 6.0 0.2681 0.3526 197
-0.054448 0.013417 11 11.0 0.4315 0.3625 197
-0.053599 0.052749 22 22.0 0.5519 0.5999 197
-0.029409 0.005219 44 44.0 0.5514 0.6246 197
-0.021991 0.014401 87 87.0 0.5140 0.4801 197
-0.015192 0.008392 174 174.0 0.5596 0.5443 197
-0.010529 0.005867 348 348.0 0.5475 0.5316 197
-0.006646 0.002762 696 696.0 0.3421 0.3795 197
-0.004007 0.001367 1392 1392.0 0.4996 0.5423 197
-0.002428 0.000850 2784 2784.0 0.5090 0.5234 197
-0.001479 0.000529 5568 5568.0 0.6413 0.6282 197
-0.001100 0.000722 11135 11135.0 0.3869 0.4154 197
+0.146961 0.146961 3 3.0 0.5498 0.2139 197
+0.088648 0.030335 6 6.0 0.2681 0.3526 197
+0.054454 0.013420 11 11.0 0.4315 0.3625 197
+0.053602 0.052750 22 22.0 0.5519 0.5997 197
+0.029411 0.005220 44 44.0 0.5514 0.6246 197
+0.021991 0.014399 87 87.0 0.5140 0.4802 197
+0.015191 0.008391 174 174.0 0.5596 0.5442 197
+0.010529 0.005866 348 348.0 0.5475 0.5316 197
+0.006645 0.002762 696 696.0 0.3421 0.3795 197
+0.004006 0.001366 1392 1392.0 0.4996 0.5423 197
+0.002427 0.000849 2784 2784.0 0.5090 0.5234 197
+0.001478 0.000529 5568 5568.0 0.6413 0.6282 197
+0.001100 0.000721 11135 11135.0 0.3869 0.4154 197
0.000929 0.000758 22269 22269.0 0.5063 0.5059 197
-0.000975 0.001022 44537 44537.0 0.4905 0.4694 197
+0.000975 0.001021 44537 44537.0 0.4905 0.4694 197
finished run
number of examples = 74746
weighted example sum = 6.952e+04
weighted label sum = 3.511e+04
-average loss = 0.00102
+average loss = 0.001019
best constant = 0.5051
best constant's loss = 0.25
total feature number = 14724962