gistfile1.txt

"C:\Program Files\Java\jdk1.8.0_221\bin\java.exe" "-javaagent:C:\Program Files\JetBrains\IntelliJ IDEA 2019.2.3\lib\idea_rt.jar=49726:C:\Program Files\JetBrains\IntelliJ IDEA 2019.2.3\bin" -Dfile.encoding=UTF-8 -classpath C:\Users\zhaoy\AppData\Local\Temp\classpath1793451622.jar com.nari.bdp.mine_server_test_behavior.classification.DNNClassificationTest
/C:/Users/zhaoy/IdeaProjects/github/gitedu/bdp-mine.git/mine/test_behavior/target/classes/test_xml/bdp/regression/jiangningRNN.xml
[INFO ] 2020-01-12 23:32:13 [main] c.n.b.m.e.service.MineJobExecutor - =========开始执行=========
########### className = com.nari.bdp.mine.cloud.dp.setrole.behavior.SetroleBehavior
########### className = com.nari.bdp.mine.cloud.io.readdatabank.behavior.ReadDataBankBehavior
########### className = com.nari.bdp.mine.classification.rnn.behavior.RNNClassifyBehavior
 cost time: 0.550000s
[INFO ] 2020-01-12 23:32:13 [main] c.n.b.m.c.i.r.b.ReadDataBankBehavior - ===========开始执行 com.nari.bdp.mine.cloud.io.readdatabank.behavior.ReadDataBankBehavior节点=============
文件数据源 cost time: 17.178000s
Temp--static column：factor0,factor1,factor2,factor3,factor4 used 2.819 seconds
Temp--static column：null,null,null,null,null,null used 0.0 seconds
+-----+-------+-------+-------+-------+-------+
|label|factor0|factor1|factor2|factor3|factor4|
+-----+-------+-------+-------+-------+-------+
|    1|      5|    6.7|      3|      5|      3|
|    1|      4|    4.3|      1|      1|      0|
|    1|      5|    5.8|      4|      5|      3|
|    0|      4|    2.8|      1|      1|      3|
|    1|      5|    7.4|      1|      5|      0|
|    0|      4|    6.5|      1|      0|      3|
|    0|      4|    7.0|      0|      0|      3|
|    0|      5|    4.2|      1|      0|      3|
|    1|      5|    5.7|      1|      5|      3|
|    1|      5|    6.0|      0|      5|      1|
|    1|      5|    7.6|      1|      4|      3|
|    1|      3|    4.2|      2|      1|      3|
|    0|      4|    6.4|      1|      0|      3|
|    0|      4|    3.6|      3|      1|      2|
|    0|      4|    6.0|      2|      1|      2|
|    0|      4|    5.4|      1|      1|      3|
|    0|      3|    5.2|      3|      4|      3|
|    1|      4|    5.9|      2|      1|      3|
|    1|      4|    5.4|      1|      1|      3|
|    1|      5|    4.5|      4|      5|      3|
+-----+-------+-------+-------+-------+-------+
only showing top 20 rows

设置角色 cost time: 0.333000s
LSTMClassificationOperator begin 
+-----+-------+-------+-------+-------+-------+-------------+--------------------+--------------------+
|label|factor0|factor1|factor2|factor3|factor4|label_numeric|       featureoutput|    featureoutputStd|
+-----+-------+-------+-------+-------+-------+-------------+--------------------+--------------------+
|    1|      5|    6.7|      3|      5|      3|          1.0|[5.0,6.7,3.0,5.0,...|[0.83333333333333...|
|    1|      4|    4.3|      1|      1|      0|          1.0|[4.0,4.3,1.0,1.0,...|[0.66666666666666...|
|    1|      5|    5.8|      4|      5|      3|          1.0|[5.0,5.8,4.0,5.0,...|[0.83333333333333...|
|    0|      4|    2.8|      1|      1|      3|          0.0|[4.0,2.8,1.0,1.0,...|[0.66666666666666...|
|    1|      5|    7.4|      1|      5|      0|          1.0|[5.0,7.4,1.0,5.0,...|[0.83333333333333...|
|    0|      4|    6.5|      1|      0|      3|          0.0|[4.0,6.5,1.0,0.0,...|[0.66666666666666...|
|    0|      4|    7.0|      0|      0|      3|          0.0|[4.0,7.0,0.0,0.0,...|[0.66666666666666...|
|    0|      5|    4.2|      1|      0|      3|          0.0|[5.0,4.2,1.0,0.0,...|[0.83333333333333...|
|    1|      5|    5.7|      1|      5|      3|          1.0|[5.0,5.7,1.0,5.0,...|[0.83333333333333...|
|    1|      5|    6.0|      0|      5|      1|          1.0|[5.0,6.0,0.0,5.0,...|[0.83333333333333...|
|    1|      5|    7.6|      1|      4|      3|          1.0|[5.0,7.6,1.0,4.0,...|[0.83333333333333...|
|    1|      3|    4.2|      2|      1|      3|          1.0|[3.0,4.2,2.0,1.0,...|[0.5,0.4375000000...|
|    0|      4|    6.4|      1|      0|      3|          0.0|[4.0,6.4,1.0,0.0,...|[0.66666666666666...|
|    0|      4|    3.6|      3|      1|      2|          0.0|[4.0,3.6,3.0,1.0,...|[0.66666666666666...|
|    0|      4|    6.0|      2|      1|      2|          0.0|[4.0,6.0,2.0,1.0,...|[0.66666666666666...|
|    0|      4|    5.4|      1|      1|      3|          0.0|[4.0,5.4,1.0,1.0,...|[0.66666666666666...|
|    0|      3|    5.2|      3|      4|      3|          0.0|[3.0,5.2,3.0,4.0,...|[0.5,0.5416666666...|
|    1|      4|    5.9|      2|      1|      3|          1.0|[4.0,5.9,2.0,1.0,...|[0.66666666666666...|
|    1|      4|    5.4|      1|      1|      3|          1.0|[4.0,5.4,1.0,1.0,...|[0.66666666666666...|
|    1|      5|    4.5|      4|      5|      3|          1.0|[5.0,4.5,4.0,5.0,...|[0.83333333333333...|
+-----+-------+-------+-------+-------+-------+-------------+--------------------+--------------------+
only showing top 20 rows

fit Epochs ... ... 0
fit Epochs ... ... 1
fit Epochs ... ... 2
fit Epochs ... ... 3
fit Epochs ... ... 4
fit Epochs ... ... 5
fit Epochs ... ... 6
fit Epochs ... ... 7
fit Epochs ... ... 8
fit Epochs ... ... 9
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fit Epochs ... ... 11
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fit Epochs ... ... 14
fit Epochs ... ... 15
fit Epochs ... ... 16
fit Epochs ... ... 17
fit Epochs ... ... 18
fit Epochs ... ... 19
fit Epochs ... ... 20
fit Epochs ... ... 21
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fit Epochs ... ... 23
fit Epochs ... ... 24
fit Epochs ... ... 25
fit Epochs ... ... 26
fit Epochs ... ... 27
fit Epochs ... ... 28
fit Epochs ... ... 29
preModel.getisApplymodel = false
in getTransfrom LSTMClassificationOperator end 
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p = (1.0,[0.3768691234731107,0.6231308765268894])
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p = (0.0,[0.6537840210023184,0.34621597899768175])
p = (1.0,[0.18347386329318674,0.8165261367068133])
p = (0.0,[0.7018591504380355,0.2981408495619645])
p = (1.0,[0.4100823369932015,0.5899176630067984])
p = (0.0,[0.6153396669515964,0.38466033304840364])
p = (1.0,[0.22274977713302196,0.7772502228669781])
p = (1.0,[0.21335508959681276,0.7866449104031872])
p = (1.0,[0.45644397989330215,0.5435560201066978])
p = (0.0,[0.716351850134361,0.28364814986563897])
p = (1.0,[0.25939377332342806,0.7406062266765719])
p = (0.0,[0.7833447143104948,0.21665528568950532])
p = (1.0,[0.4986014792156168,0.5013985207843832])
p = (0.0,[0.6322033768167482,0.3677966231832518])
p = (1.0,[0.4823452983679499,0.51765470163205])
p = (1.0,[0.4902180743549754,0.5097819256450247])
p = (0.0,[0.7710790285168372,0.22892097148316287])
p = (1.0,[0.4857666177241914,0.5142333822758087])
p = (1.0,[0.4434198606694092,0.5565801393305908])
p = (1.0,[0.38178797656399116,0.6182120234360089])
p = (0.0,[0.5137160044273389,0.48628399557266105])
p = (0.0,[0.5615372852534976,0.4384627147465025])
p = (0.0,[0.8773326473119144,0.12266735268808562])
p = (1.0,[0.1681382233476615,0.8318617766523385])
p = (0.0,[0.7194826460368167,0.2805173539631834])
p = (0.0,[0.9165110181470614,0.08348898185293858])
p = (1.0,[0.42770716822115745,0.5722928317788425])
p = (0.0,[0.5386880596129262,0.46131194038707374])
p = (1.0,[0.16127788085086317,0.8387221191491369])
p = (1.0,[0.3587526016122736,0.6412473983877264])
p = (0.0,[0.7242173176608027,0.2757826823391973])
p = (0.0,[0.7706576619861086,0.2293423380138913])
p = (1.0,[0.1459731756759826,0.8540268243240173])
p = (1.0,[0.19168099019146062,0.8083190098085394])
+-----+-------+-------+-------+-------+-------+----------+--------------------+-------------------+--------------------+
|label|factor0|factor1|factor2|factor3|factor4|prediction|         probability|             prob_0|              prob_1|
+-----+-------+-------+-------+-------+-------+----------+--------------------+-------------------+--------------------+
|    1|      5|    8.0|      4|      3|      3|         1|[0.54140045851217...| 0.5414004585121703|              0.5474|
|    1|      5|    6.4|      4|      5|      3|         0|[0.5591,0.3248180...|             0.5591| 0.32481803804992415|
|    0|      4|    5.3|      4|      4|      3|         1|[0.27103810110481...|0.27103810110481286|              0.6177|
|    0|      4|    4.7|      1|      1|      2|         0|[0.5318,0.0246382...|             0.5318|0.024638221140148242|
|    0|      4|    4.1|      2|      1|      3|         0|[0.9344,0.7543069...|             0.9344|  0.7543069794074151|
|    0|      4|    6.2|      2|      1|      0|         0|[0.5205,4.8659465...|             0.5205|4.865946519112540...|
|    1|      5|    3.3|      4|      4|      0|         1|[0.69509581265594...| 0.6950958126559414|               0.781|
|    0|      4|    6.2|      3|      1|      3|         1|[0.15268989973823...|0.15268989973823055|              0.5671|
|    1|      5|    5.1|      4|      4|      3|         0|[0.5319,0.1113410...|             0.5319| 0.11134103465149181|
|    0|      3|    3.4|      4|      4|      3|         0|[0.5163,0.0477080...|             0.5163| 0.04770803117713096|
|    0|      5|    6.0|      3|      1|      3|         1|[0.60280660542835...| 0.6028066054283503|              0.6656|
|    1|      5|    7.9|      4|      4|      3|         1|[0.04314276926559...|0.04314276926559457|              0.5002|
|    1|      4|    4.3|      1|      1|      0|         1|[0.6838383547158,...|    0.6838383547158|              0.7972|
|    1|      5|    5.9|      4|      4|      3|         1|[0.47332296565822...|0.47332296565822585|              0.8728|
|    0|      4|    2.9|      2|      0|      0|         1|[0.11869761637611...| 0.1186976163761182|              0.5108|
|    1|      5|    8.1|      3|      4|      3|         0|[0.5999,0.3365355...|             0.5999|   0.336535522859136|
|    0|      4|    5.1|      0|      0|      3|         1|[0.13064225013401...| 0.1306422501340172|              0.7672|
|    1|      5|    5.7|      4|      5|      3|         0|[0.8543,0.4273096...|             0.8543| 0.42730960793489614|
|    0|      5|    6.6|      4|      4|      4|         1|[0.10336269515914...| 0.1033626951591462|              0.5754|
|    0|      4|    5.4|      1|      1|      0|         0|[0.8328,0.1621554...|             0.8328| 0.16215542422498008|
+-----+-------+-------+-------+-------+-------+----------+--------------------+-------------------+--------------------+
only showing top 20 rows

root
 |-- label: string (nullable = true)
 |-- factor0: integer (nullable = true)
 |-- factor1: double (nullable = true)
 |-- factor2: integer (nullable = true)
 |-- factor3: integer (nullable = true)
 |-- factor4: integer (nullable = true)
 |-- prediction: string (nullable = true)
 |-- probability: vector (nullable = false)
 |-- prob_0: double (nullable = true)
 |-- prob_1: double (nullable = true)

RNN分类 cost time: 371.061000s
Temp--static column：factor0,factor1,factor2,factor3,factor4,prob_0,prob_1 used 1.09 seconds
Temp--static column：null,null,null,null,null,null,null,null,null,null used 0.0 seconds
com.meritdata.tempo.force.exit is:null

Process finished with exit code 1024