diff options
| author | Hal Daume III <me@hal3.name> | 2013-01-11 02:33:01 +0400 |
|---|---|---|
| committer | Hal Daume III <me@hal3.name> | 2013-01-11 02:33:01 +0400 |
| commit | 36f6820ef0cd06219c4a0235edb462aaa2a5d74f (patch) | |
| tree | 365fc06b4b0468bb2b7940906389900f9774775e /test/train-sets/ref/rcv1_small.stderr | |
| parent | bd16dfed49131573b56e134aae9af0d0fed5350b (diff) | |
minor bug fix
Diffstat (limited to 'test/train-sets/ref/rcv1_small.stderr')
| -rw-r--r-- | test/train-sets/ref/rcv1_small.stderr | 36 |
1 files changed, 18 insertions, 18 deletions
diff --git a/test/train-sets/ref/rcv1_small.stderr b/test/train-sets/ref/rcv1_small.stderr index 0519bd31..361c6ec0 100644 --- a/test/train-sets/ref/rcv1_small.stderr +++ b/test/train-sets/ref/rcv1_small.stderr @@ -11,23 +11,23 @@ Allocated 72M for weights and mem creating cache_file = train-sets/rcv1_small.dat.cache Reading from train-sets/rcv1_small.dat num sources = 1 - 1 0.69315 0.01247 109.37472 165.25443 1072660.62500 0.66186 0.299 - 3 24.96380 0.09448 58.49783 -0.335275 -0.667864 (revise x 0.5) 0.33093 0.346 - 4 6.68890 0.07916 21.38882 -0.165651 -0.341257 (revise x 0.5) 0.16546 0.406 - 5 2.02595 0.05334 9.61256 -0.073645 -0.172136 (revise x 0.5) 0.08273 0.471 - 6 0.88609 0.02271 4.21489 -0.021323 -0.077380 (revise x 0.5) 0.04137 0.532 - 7 0.65787 0.00567 2.42293 0.007797 -0.022375 (revise x 0.5) 0.02068 0.599 - 8 0.64090 0.00109 2.53848 0.023094 0.007617 5.59308 1.00000 0.790 - 9 0.59157 0.00084 1.98472 0.939813 0.880475 449.76346 1.00000 0.989 -10 0.36198 0.00015 0.22195 0.590336 0.255459 123.06654 1.00000 1.218 -11 0.34817 0.00506 0.68002 0.218971 -0.427074 27.43073 1.00000 1.483 -12 0.32328 0.00029 0.08338 0.597310 0.217821 3.59897 1.00000 1.806 -13 0.31983 0.00001 0.04912 0.738427 0.480963 8.91283 1.00000 2.140 -14 0.31597 0.00006 0.04996 0.762547 0.528463 24.29690 1.00000 2.503 -15 0.31083 0.00018 0.05458 0.726800 0.455733 103.02335 1.00000 2.892 -16 0.29800 0.00004 0.01069 0.692399 0.384369 50.95579 1.00000 3.289 -17 0.29486 0.00000 0.00018 0.516694 0.031776 0.39481 1.00000 3.807 -18 0.29479 0.00000 0.00009 0.595978 0.192369 0.24621 1.00000 4.210 + 1 0.69315 0.01247 109.37472 165.25444 1072660.62500 0.66186 0.309 + 3 24.96380 0.09448 58.49783 -0.335275 -0.667864 (revise x 0.5) 0.33093 0.365 + 4 6.68890 0.07916 21.38882 -0.165651 -0.341257 (revise x 0.5) 0.16546 0.483 + 5 2.02595 0.05334 9.61256 -0.073645 -0.172136 (revise x 0.5) 0.08273 0.599 + 6 0.88609 0.02271 4.21489 -0.021323 -0.077380 (revise x 0.5) 0.04137 0.666 + 7 0.65787 0.00567 2.42293 0.007797 -0.022375 (revise x 0.5) 0.02068 0.739 + 8 0.64090 0.00109 2.53848 0.023094 0.007617 5.59308 1.00000 0.925 + 9 0.59157 0.00084 1.98472 0.939814 0.880475 449.76361 1.00000 1.133 +10 0.36198 0.00015 0.22195 0.590336 0.255459 123.06779 1.00000 1.375 +11 0.34818 0.00506 0.68004 0.218960 -0.427093 27.43001 1.00000 1.649 +12 0.32328 0.00029 0.08338 0.597312 0.217825 3.59904 1.00000 1.953 +13 0.31983 0.00001 0.04912 0.738423 0.480952 8.91247 1.00000 2.298 +14 0.31597 0.00006 0.04996 0.762549 0.528469 24.29697 1.00000 2.681 +15 0.31083 0.00018 0.05458 0.726800 0.455732 103.02180 1.00000 3.103 +16 0.29800 0.00004 0.01069 0.692401 0.384374 50.95761 1.00000 3.733 +17 0.29486 0.00000 0.00018 0.516695 0.031777 0.39479 1.00000 4.107 +18 0.29479 0.00000 0.00009 0.596026 0.192467 0.24629 1.00000 4.486 finished run number of examples = 200000 @@ -36,5 +36,5 @@ weighted label sum = -1.272e+04 average loss = 0.4485 best constant = -0.06361 total feature number = 15587880 -19 0.29476 0.00000 0.00003 0.619528 0.238282 0.15641 1.00000 4.608 +19 0.29476 0.00000 0.00003 0.619462 0.238168 0.15641 1.00000 4.890 |