Can some one enlight me regarding the results of megatest?
"Steve" <[email protected]>
| Newsgroups | gmane.mail.spam.crm114 |
|---|---|
| Message-ID | <[email protected]> |
Hello list I never manage to 100% understand what the result of megatest is telling me. For example this one: ------------------------------------ # # This runs a moderately interesting set of base tests # to exercise much of CRM114 under TRE. This takes about # 1 minute to run on a 1.6 GHz Pentium-M laptop. Please # be patient; you (hopefully) won't see anything till the # full set of tests complete. If you didn't use TRE, all # bets are off. # # Lines of output that start with OK_IF_mumble are allowed # to change values. No other lines should. If other lines # do change, either your kit isn't quite right or your # install is broken (or you've found a bug). # ./megatest.sh > megatest_test.log 2>&1 diff megatest_knowngood.log megatest_test.log & sleep 1 208,209c208,209 < OK_IF_PID_CHANGES: one... MINION PROC PID: 9467 from-pipe: 6 to-pipe: 5 < OK_IF_PID_SAME_AS_ABOVE: again... MINION PROC PID: 9467 from-pipe: 6 to-pipe: 5 --- > OK_IF_PID_CHANGES: one... MINION PROC PID: 32274 from-pipe: 6 to-pipe: 5 > OK_IF_PID_SAME_AS_ABOVE: again... MINION PROC PID: 32274 from-pipe: 6 to-pipe: 5 546c546 < OK_IF_SIZE_CHANGES: Size of isolation at start: 2099035 --- > OK_IF_SIZE_CHANGES: Size of isolation at start: 2099037 550c550 < OK_IF_SIZE_CHANGES: Final isolation size: 2099052 --- > OK_IF_SIZE_CHANGES: Final isolation size: 2099054 557c557 < OK_IF_SIZE_CHANGES: Size of isolation at start: 2101517 --- > OK_IF_SIZE_CHANGES: Size of isolation at start: 2101519 561c561 < OK_IF_SIZE_CHANGES: Final isolation size: 2101532 --- > OK_IF_SIZE_CHANGES: Final isolation size: 2101534 566c566 < OK_IF_SIZE_CHANGES: Final isolation size: 2101538 --- > OK_IF_SIZE_CHANGES: Final isolation size: 2101540 571c571 < OK_IF_SIZE_CHANGES: Final isolation size: 2101539 --- > OK_IF_SIZE_CHANGES: Final isolation size: 2101541 576c576 < OK_IF_SIZE_CHANGES: Final isolation size: 2101539 --- > OK_IF_SIZE_CHANGES: Final isolation size: 2101541 980a981,990 > > ./crm114: *WARNING* > neural: failed to converge within the training limit. Beware your results. > You might want to consider a larger network as well. > I'll try to keep working. > This happened at line 2 of file (from command line) > (runtime system location: crm_neural_net.c(1678) in routine: crm_neural_net_learn) > The line was: > --> learn < neural refute fromstart > (q_test.css) > <-- 982,983c992,993 < CLASSIFY fails; success probability: 0.241661 pR: -62.5048 < Best match to file #1 (q_test.css) prob: 0.7583 pR: 62.5048 --- > CLASSIFY fails; success probability: 0.324688 pR: -7.7780 > Best match to file #1 (q_test.css) prob: 0.6753 pR: 7.7780 985,986c995,996 < #0 (i_test.css): prob: 2.42e-01, pR: -62.50 < #1 (q_test.css): prob: 7.58e-01, pR: 62.50 --- > #0 (i_test.css): prob: 3.25e-01, pR: -7.78 > #1 (q_test.css): prob: 6.75e-01, pR: 7.78 989,990c999,1000 < CLASSIFY succeeds; success probability: 0.889200 pR: 189.2001 < Best match to file #0 (i_test.css) prob: 0.8892 pR: 189.2001 --- > CLASSIFY succeeds; success probability: 0.521953 pR: 0.2195 > Best match to file #0 (i_test.css) prob: 0.5220 pR: 0.2195 992,993c1002,1003 < #0 (i_test.css): prob: 8.89e-01, pR: 189.20 < #1 (q_test.css): prob: 1.11e-01, pR: -189.20 --- > #0 (i_test.css): prob: 5.22e-01, pR: 0.22 > #1 (q_test.css): prob: 4.78e-01, pR: -0.22 999,1000c1009,1010 < CLASSIFY fails; success probability: 0.017262 pR: -282.7380 < Best match to file #1 (q_test.css) prob: 0.9827 pR: 282.7380 --- > CLASSIFY fails; success probability: 0.002674 pR: -297.3258 > Best match to file #1 (q_test.css) prob: 0.9973 pR: 297.3258 1002,1003c1012,1013 < #0 (i_test.css): prob: 1.73e-02, pR: -282.74 < #1 (q_test.css): prob: 9.83e-01, pR: 282.74 --- > #0 (i_test.css): prob: 2.67e-03, pR: -297.33 > #1 (q_test.css): prob: 9.97e-01, pR: 297.33 1006,1007c1016,1017 < CLASSIFY succeeds; success probability: 0.971915 pR: 271.9152 < Best match to file #0 (i_test.css) prob: 0.9719 pR: 271.9152 --- > CLASSIFY succeeds; success probability: 0.924445 pR: 224.4452 > Best match to file #0 (i_test.css) prob: 0.9244 pR: 224.4452 1009,1010c1019,1020 < #0 (i_test.css): prob: 9.72e-01, pR: 271.92 < #1 (q_test.css): prob: 2.81e-02, pR: -271.92 --- > #0 (i_test.css): prob: 9.24e-01, pR: 224.45 > #1 (q_test.css): prob: 7.56e-02, pR: -224.45 1015,1016c1025,1026 < CLASSIFY succeeds; success probability: 0.8901 pR: 9.0850 < Best match to file #0 (i_test.css) prob: 0.8901 pR: 9.0850 --- > CLASSIFY succeeds; success probability: 0.8872 pR: 8.9571 > Best match to file #0 (i_test.css) prob: 0.8872 pR: 8.9571 1018,1019c1028,1029 < #0 (i_test.css): documents: 300, features: 7464, prob: 8.90e-01, pR: 9.09 < #1 (q_test.css): documents: 175, features: 6223, prob: 1.10e-01, pR: -9.09 --- > #0 (i_test.css): documents: 300, features: 7464, prob: 8.87e-01, pR: 8.96 > #1 (q_test.css): documents: 175, features: 6223, prob: 1.13e-01, pR: -8.96 1022,1023c1032,1033 < CLASSIFY succeeds; success probability: 0.9947 pR: 22.7433 < Best match to file #0 (i_test.css) prob: 0.9947 pR: 22.7433 --- > CLASSIFY succeeds; success probability: 0.9947 pR: 22.7512 > Best match to file #0 (i_test.css) prob: 0.9947 pR: 22.7512 1025,1026c1035,1036 < #0 (i_test.css): documents: 300, features: 7464, prob: 9.95e-01, pR: 22.74 < #1 (q_test.css): documents: 175, features: 6223, prob: 5.29e-03, pR: -22.74 --- > #0 (i_test.css): documents: 300, features: 7464, prob: 9.95e-01, pR: 22.75 > #1 (q_test.css): documents: 175, features: 6223, prob: 5.28e-03, pR: -22.75 1031,1032c1041,1042 < CLASSIFY succeeds; success probability: 0.8723 pR: 8.3442 < Best match to file #0 (i_test.css) prob: 0.8723 pR: 8.3442 --- > CLASSIFY succeeds; success probability: 0.8725 pR: 8.3523 > Best match to file #0 (i_test.css) prob: 0.8725 pR: 8.3523 1034,1035c1044,1045 < #0 (i_test.css): documents: 300, features: 34780, prob: 8.72e-01, pR: 8.34 < #1 (q_test.css): documents: 175, features: 32300, prob: 1.28e-01, pR: -8.34 --- > #0 (i_test.css): documents: 300, features: 34780, prob: 8.72e-01, pR: 8.35 > #1 (q_test.css): documents: 175, features: 32300, prob: 1.28e-01, pR: -8.35 1038,1039c1048,1049 < CLASSIFY succeeds; success probability: 0.9678 pR: 14.7738 < Best match to file #0 (i_test.css) prob: 0.9678 pR: 14.7738 --- > CLASSIFY succeeds; success probability: 0.9678 pR: 14.7733 > Best match to file #0 (i_test.css) prob: 0.9678 pR: 14.7733 1063,1064c1073,1074 < CLASSIFY succeeds; success probability: 0.8890 pR: 9.0370 < Best match to file #0 (i_test.css) prob: 0.8890 pR: 9.0370 --- > CLASSIFY succeeds; success probability: 0.8889 pR: 9.0322 > Best match to file #0 (i_test.css) prob: 0.8889 pR: 9.0322 1066,1067c1076,1077 < #0 (i_test.css):documents: 300, features: 42397, prob: 8.89e-01, pR: 9.04 < #1 (q_test.css):documents: 175, features: 37599, prob: 1.11e-01, pR: -9.04 --- > #0 (i_test.css):documents: 300, features: 42397, prob: 8.89e-01, pR: 9.03 > #1 (q_test.css):documents: 175, features: 37599, prob: 1.11e-01, pR: -9.03 1070,1071c1080,1081 < CLASSIFY succeeds; success probability: 0.9848 pR: 18.1080 < Best match to file #0 (i_test.css) prob: 0.9848 pR: 18.1080 --- > CLASSIFY succeeds; success probability: 0.9847 pR: 18.0999 > Best match to file #0 (i_test.css) prob: 0.9847 pR: 18.0999 1073,1074c1083,1084 < #0 (i_test.css):documents: 300, features: 42397, prob: 9.85e-01, pR: 18.11 < #1 (q_test.css):documents: 175, features: 37599, prob: 1.52e-02, pR: -18.11 --- > #0 (i_test.css):documents: 300, features: 42397, prob: 9.85e-01, pR: 18.10 > #1 (q_test.css):documents: 175, features: 37599, prob: 1.53e-02, pR: -18.10 ------------------------------------ I understand those with OK_IF_mumble but what bout the others? Most of them have one positive value and then one negative value with the exact same number. So the difference there is just the sign. Is this an issue? And what about the others like this one: ----------------------------------- 1006,1007c1016,1017 < CLASSIFY succeeds; success probability: 0.971915 pR: 271.9152 < Best match to file #0 (i_test.css) prob: 0.9719 pR: 271.9152 --- > CLASSIFY succeeds; success probability: 0.924445 pR: 224.4452 > Best match to file #0 (i_test.css) prob: 0.9244 pR: 224.4452 ----------------------------------- The pR seems to be equal but the probability digits are not the same. Is this an issue? The above result is from crm114-20080326-BlameSentansoken compiled with Intel C/C++ compiler v10.1.017. // Steve -- GMX Kostenlose Spiele: Einfach online spielen und Spaß haben mit Pastry Passion! http://games.entertainment.gmx.net/de/entertainment/games/free/puzzle/6169196 ------------------------------------------------------------------------- This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK & win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100&url=/